This draft defines Attenuating Authorization Tokens (AATs), a JWT-based format that allows cryptographically enforced capability delegation chains for AI agents where each delegation step can only narrow permissions, never expand them. The system extends OAuth Rich Authorization Requests with offline verifiable constraint propagation for tool invocation permissions.

Notable originality in applying cryptographic attenuation principles to AI agent authorization with offline verification of delegation chains

Detailed specification with concrete protocol mechanisms, JWT extensions, and verification algorithms, though implementation examples could be stronger

Minor conceptual overlap with general OAuth delegation patterns but unique approach to cryptographic capability attenuation for agents

Single revision draft with no clear working group adoption signals yet

Directly addresses core AI agent authorization challenges with practical delegation semantics for multi-agent systems

Agent identity/auth
A2A protocols
AI safety/alignment


This draft extends OAuth Transaction Tokens to support agent context propagation in multi-agent workflows. It defines mechanisms to identify agents performing actions while preserving principal identity context across agent transitions in complex call chains.

Useful extension of existing OAuth mechanisms for agent-specific use cases, though builds incrementally on established patterns

Well-detailed specification with clear protocol mechanisms, structured claims definitions, and coverage of both single and multi-agent scenarios

Shares core concepts with OAuth Transaction Tokens and RFC8693, but applies them specifically to agent contexts

Single revision with future date suggests early stage, limited evidence of community engagement or working group adoption

Directly addresses core challenges in agent identity and authentication for multi-agent systems and autonomous workflows


This draft proposes a framework for mapping service flow characteristics to network resources in multi-modal intelligent computing networks using ALTO protocol and SDN architecture. It focuses on dynamic resource allocation and network optimization through intelligent mapping techniques.

Incremental work combining existing ALTO protocol with SDN for service flow mapping - straightforward application of known technologies

Early architectural sketch without detailed protocol specifications, implementation details, or concrete examples

Significant overlap with existing SDN traffic engineering and ALTO-based network optimization work

No evidence of working group adoption or community engagement, appears to be individual submission

Partially relevant - addresses intelligent network management but focuses more on traditional network optimization than AI agents


This draft defines the Agent-to-Tool (A2T) Protocol that standardizes how AI agents discover and invoke third-party tools/APIs. It provides enumeration capabilities for tool discovery and invocation mechanisms for runtime execution.

Useful contribution addressing practical AI agent integration needs, though tool invocation patterns are becoming established

Defined protocol with clear enumeration and invocation APIs, but lacks detailed implementation examples and edge case handling

Shares conceptual space with OpenAI function calling specs and general API integration patterns, but focuses on standardized discovery

Single revision from 2026 with no clear working group adoption or community feedback visible

Core AI agent functionality - tool integration is fundamental to practical agent deployment in enterprise environments

A2A protocols
Data formats/interop
Agent discovery/reg


This draft proposes using the Model Context Protocol (MCP) to enable network devices to act as MCP servers and controllers as clients for LLM-based network troubleshooting. It extends the model to support device-to-device collaboration for distributed fault correlation when controllers are unreachable.

Useful application of existing MCP standard to network domain with reasonable D2D extension

Defines protocol mapping and architecture but lacks detailed implementation specifics

Some conceptual overlap with intent-based networking but novel MCP application

Single revision with future date suggests early stage development

Directly addresses AI-driven network automation with LLM integration

Autonomous netops
A2A protocols
Data formats/interop


Lisp-Nexagon combines LISP with H3 spatial indexing to create a geospatial intelligence network for distributed agents in transportation, public safety, and logistics applications. The protocol enables agents to report, aggregate, and disseminate location-based state information across physical-world systems.

Novel combination of LISP networking with H3 geospatial indexing for agent-based geo-intelligence - creative architectural fusion

Defined protocol concept with clear architecture but likely needs more implementation details and examples

Some conceptual overlap with location-based networking but the H3+LISP combination appears relatively unique

Recent draft suggesting active development, though unclear about broader community engagement at this stage

Directly relevant to AI agents operating in physical world scenarios with geospatial coordination needs


This draft proposes network-layer infrastructure to give AI agents first-class network citizenship, moving beyond current application-layer HTTP-based communication. It identifies the need for agent-specific addressing, identity, and transport mechanisms independent of web infrastructure designed for humans.

Notable originality in recognizing agents as a distinct network participant class requiring dedicated network-layer support rather than just application protocols

Problem statement only with requirements identification but no technical solutions or protocol mechanisms defined

Minor conceptual similarities to general identity/addressing work but unique focus on agent-specific network layer needs

Single revision with future date suggests early stage without demonstrated community engagement or WG activity

Core AI agent topic addressing fundamental networking infrastructure for autonomous agent communication

A2A protocols
Agent identity/auth
Agent discovery/reg


This draft proposes a protocol-agnostic data model for multi-agent communication in Level 4 autonomous networks, enabling intelligent agents to interact securely and efficiently for self-management and healing. The model aims to support end-to-end task execution and closed-loop operations across network services and resource layers.

Useful contribution addressing multi-agent coordination in autonomous networks, though builds on established autonomous networking concepts

Early sketch stage - presents the problem and high-level model concept but lacks detailed protocol specifications or implementation details

Shares conceptual overlap with existing autonomous network management and multi-agent system drafts, but focuses specifically on protocol-agnostic interaction models

Single revision from January 2026 with no clear working group adoption or community engagement visible

Core AI agent topic directly addressing multi-agent interaction models for autonomous network operations

A2A protocols
Autonomous netops
Data formats/interop


Proposes a comprehensive evaluation framework for LLM-based network configuration agents, combining emulator environments, representative tasks, and multi-dimensional metrics. The framework aims to enable reproducible comparisons of intent-driven network configuration approaches using standardized assessment criteria.

Useful contribution addressing the gap in standardized evaluation methods for LLM network agents, though evaluation frameworks are a natural extension of existing ML benchmarking practices

Detailed specification with concrete framework components, task definitions, and evaluation metrics, appears implementation-ready with clear technical structure

Minor similarities to general ML evaluation practices but unique focus on network configuration domain with specialized metrics and emulator integration

Single revision draft with recent publication date, no clear indication of working group adoption or broader community engagement yet

Core AI agent topic directly addressing evaluation and benchmarking of LLM agents in network operations context


Defines a reason:// URI scheme and registry protocol for storing and retrieving compressed reasoning artifacts from autonomous agents. Artifacts enter the registry through competitive arbitration scored by the Web Agent Reasoning Federation (WARF) protocol, creating DNS-like infrastructure for the agentic internet.

Genuinely novel approach combining URI schemes, competitive arbitration, and structural reasoning artifacts with mathematical non-invertibility - no existing work addresses this specific combination

Early sketch stage - describes high-level concept and competitive mechanism but lacks detailed protocol specification, message formats, or implementation guidance

Unique approach - while URI schemes and registries exist, the combination with competitive reasoning artifact arbitration and WARF scoring is distinctive

Single revision with future date (2026-03-30) suggests early conceptual work without demonstrated community engagement or working group adoption

Core AI agent topic directly addressing infrastructure needs for distributed autonomous agent networks and reasoning artifact management

A2A protocols
Agent discovery/reg
Data formats/interop


This draft defines protocol bindings for AI preferences in real-time communications, specifying how SIP and SDP can carry AI processing requirements and constraints. It provides concrete header fields and attributes for endpoints and AI assistants to negotiate AI-driven processing of session data.

Notable approach to integrate AI preferences directly into established real-time protocols like SIP/SDP, addressing a gap in how AI capabilities are signaled in communications

Defines specific protocol mechanisms and binding models with concrete SIP headers and SDP attributes, though implementation details and examples could be more comprehensive

While builds on existing SIP/SDP foundations, the AI preference binding approach appears relatively unique with minor conceptual overlap to other AI signaling work

Single revision from February 2026 with no clear indication of working group adoption or broader community engagement yet

Core AI agent topic directly addressing how AI capabilities and preferences are signaled and negotiated in real-time communication protocols


IntelliNode proposes an in-network intelligent scheduling mechanism for CATS that uses FPGAs and programmable switches to perform real-time scheduling decisions for AI workloads. It creates a closed-loop system that extracts features at line rate and makes heuristic decisions for path selection, tensor slicing, and compute matching.

Notable originality in combining FPGA-based in-network processing with AI workload-aware scheduling, moving beyond traditional probe-based approaches

Single revision from 2026 with no indication of working group adoption or community feedback yet

Minor similarities to CATS framework extensions but introduces unique FPGA-based in-network intelligence approach not seen in other drafts

Directly relevant to AI agent networking as it addresses intelligent traffic steering and scheduling for distributed AI training/inference workloads


This draft presents problem statement, use cases, and requirements for Distributed Inference Network (DIN) architecture to address scalability, latency, and security challenges of centralized AI inference through edge-cloud collaboration. It focuses on enabling low-latency, high-concurrency AI inference services across distributed network infrastructure.

Incremental contribution applying well-known edge computing and CDN distribution concepts to AI inference workloads, without novel architectural insights

Problem statement phase only, lacking concrete technical mechanisms, protocols, or implementation details for the proposed DIN architecture

Significant overlap with existing edge computing, mobile edge computing (MEC), and distributed AI serving literature and standards work

Single revision draft with no clear working group adoption or broader community engagement visible

Directly addresses AI inference infrastructure challenges, which is highly relevant to AI agent deployment and scalability requirements

Model serving/inference
ML traffic mgmt
Autonomous netops


This draft proposes a Massive Data Transmission (MDT) framework for efficiently utilizing nighttime idle bandwidth in high BDP networks through terminal-driven intelligent parameter optimization. The system adjusts local configurations like disk I/O, NIC bandwidth, and TCP buffers to match transmission goals for services like same-day delivery.

Incremental improvement to existing bandwidth optimization and traffic management techniques, applying known concepts to nighttime idle periods

Early sketch with high-level architecture described but lacking detailed protocol specifications, implementation details, or concrete mechanisms

Shares traffic management and QoS optimization concepts with existing network management drafts, though specific focus on nighttime bandwidth utilization is somewhat distinct

Single revision draft with no evidence of working group adoption or broader community engagement

Tangentially related through mentions of 'intelligent parameter optimization' but primarily focuses on traditional network traffic management rather than AI agents


FADP defines an HTTP extension that allows AI agents to pay for web resources using cryptocurrency micropayments, embedding cryptographic payment proofs in HTTP headers. The protocol extends HTTP 402 with new headers for payment requirements and verification, targeting sub-dollar transactions where traditional billing is impractical.

Notable integration of blockchain micropayments with HTTP for autonomous agents - novel approach to solving agent payment authentication

Detailed specification with concrete HTTP header definitions, nonce mechanisms, and verification flows - appears implementation-ready

Some conceptual similarity to HTTP payment extensions but unique in blockchain integration and agent-specific design

Single draft submission with no clear working group adoption or community engagement indicators

Directly addresses core autonomous agent needs for resource access and payment authentication in decentralized scenarios


The Crovia Seal defines a cryptographic receipt format using Ed25519 signatures and hash chains to provide tamper-evident provenance records for AI-generated content. The specification includes optional transparency log integration and witness co-signatures for enhanced verification.

Useful contribution applying established cryptographic primitives (Ed25519, hash chains, transparency logs) to the emerging need for AI output provenance verification

Detailed specification with specific cryptographic choices (Ed25519, SHA-256, CSC-1 canonicalization), clear field definitions, and considerations for offline verification and third-party integration

Minor similarities to general digital signature and transparency log approaches, but specific application to AI provenance appears relatively unique

Single revision with no clear indication of working group adoption or broader community engagement yet

Directly addresses AI output authenticity and provenance, which are increasingly critical concerns for AI systems deployment and trustworthiness

Data formats/interop
AI safety/alignment
Agent identity/auth


This draft proposes adding a 'target_id' field to OAuth 2.0 to enable granular authorization for AI agents. The extension aims to provide precise permission management and enhance traceability while maintaining compatibility with existing OAuth workflows.

Adding a target identifier to OAuth is an incremental extension of existing authorization patterns, not a fundamentally new approach

Abstract suggests early-stage work with basic concept outlined but lacks detailed protocol specification or implementation guidance

Shares authorization concepts with existing OAuth extensions and fine-grained access control mechanisms, though AI agent focus is somewhat distinct

Appears to be early draft from 2026 with limited indication of broader community engagement or working group adoption

Directly addresses AI agent authorization challenges, which is highly relevant to autonomous systems requiring controlled access to resources


HTTP Events Query Protocol (EQP) enables user agents to receive event notifications directly from HTTP resources using a minimal protocol extension. The draft proposes that resources themselves should be the intuitive source for event notifications rather than separate event systems.

Incremental approach to HTTP-based event delivery, building on existing patterns but not fundamentally novel

Detailed 29-page specification with clear protocol definitions and examples, appears implementation-ready

Significant overlap with Server-Sent Events, WebSockets, and other HTTP event streaming mechanisms

Single revision draft with October 2025 date, no evidence of working group adoption or community engagement

Partially relevant as it addresses agent-to-resource communication patterns, though not specifically AI-focused


This draft establishes an IANA registry for Model Context Protocol (MCP) tool surface names, which are wire-level identifiers used by clients to invoke typed capabilities on MCP servers. It defines a Specification Required registration process with Designated Expert review and includes initial entries from related Morrison-family drafts.

Registry establishment is incremental work building on existing MCP specifications, following standard IANA patterns

Defines clear registry structure, registration procedures, and expert review process but lacks implementation examples

Builds on Morrison-family MCP drafts but represents distinct registry infrastructure component

Active development as part of broader MCP specification suite, though limited to registry mechanics

Directly supports AI agent infrastructure by standardizing tool capability identifiers in MCP ecosystem

Agent discovery/reg
Data formats/interop
A2A protocols


This draft specifies a framework for orchestrating In-Network Computing Functions (ICFs) in Cooperative Intelligent Transportation Systems, enabling vehicles, roadside units, and network domains to collaborate through Agent-to-Agent communication. The approach aims to optimize real-time V2X communications, traffic management, and edge computing services through intelligent agent coordination.

Useful contribution combining in-network computing with C-ITS through A2A paradigms, though individual concepts exist separately

Early sketch level - abstract describes framework goals but lacks concrete protocol details or implementation specifics

Shares concepts with edge computing drafts and vehicular networking work, but specific C-ITS+ICF+A2A combination has limited overlap

Single revision in NMRG, limited visibility of broader community engagement or working group momentum

Directly relevant with explicit Agent-to-Agent communication paradigm and intelligent agents coordinating computing tasks

A2A protocols
ML traffic mgmt
Autonomous netops
Agent discovery/reg


This draft proposes an Intelligence Delivery Network (IDN) framework for distributing deep learning inference models across geographically distributed servers to optimize latency, privacy, and scalability. The document presents architectural concepts and vocabulary but does not specify actual protocols or implementation details.

Incremental extension of CDN concepts to AI inference workloads, builds on established distributed computing patterns

Early architectural sketch with framework concepts but lacks concrete protocols, mechanisms, or detailed specifications

Shares distributed inference concepts with some existing work in edge AI and model serving architectures

Single draft submission with no indication of working group adoption or community development activity

Directly addresses core AI infrastructure challenges around distributed model serving and inference optimization


WLP v0 defines a protocol for translating AI-generated scientific hypotheses into machine-executable wet-lab automation instructions, specifically targeting longevity research applications. The draft provides a royalty-free schema with reference implementations in Rust and Python for AI-to-automation instruction translation.

Notable originality in bridging AI hypothesis generation with physical lab automation through structured protocols - addresses a genuinely important gap in scientific automation workflows

Defined protocol with schema specification and reference implementations mentioned, though lacks detailed examples or test vectors in the abstract

References SCP from photoresist domain but appears to be novel application to wet-lab/longevity research with minimal overlap to existing IETF work

Single revision draft with no clear indication of working group adoption or broader community engagement yet

Directly relevant to AI agent systems - specifically addresses agent-to-automation interfaces and structured instruction protocols for physical world interaction

A2A protocols
Data formats/interop
Human-agent interaction


RVP proposes a protocol for coordinating physical entities (robots, IoT devices) with digital agents (AI systems, virtual twins) through unified identity management and graph-based coordination. The draft addresses the gap between existing peer-to-peer agent protocols and the hierarchical, constraint-aware communication needed for embodied intelligence in manufacturing, smart cities, and autonomous systems.

Notable originality in bridging physical-digital agent coordination with explicit physical constraint integration and non-peer hierarchical relationships

Problem statement only - no protocol specification, message formats, or technical mechanisms defined

Minor similarities to existing agent protocols (A2A, MCP, ANP) but addresses a distinct physical-digital integration gap

Single draft submission with no evidence of working group adoption or community engagement

Core AI agent topic addressing critical embodied intelligence coordination challenges with direct relevance to physical-world AI deployment

A2A protocols
Agent identity/auth
Data formats/interop
Human-agent interaction


HJS defines an accountability layer for AI agents using four primitives (Judgment/Delegation/Termination/Verification) to record responsibility chains. The system leverages Bitcoin blockchain anchoring via Open Timestamp proofs to create immutable, court-admissible evidence of AI agent actions.

Notable originality in combining blockchain-anchored timestamping with AI agent accountability primitives, creating a novel approach to legal evidence generation for AI systems

Early sketch stage - defines core primitives and blockchain integration concept but lacks detailed protocol specification, message formats, and implementation guidance

Minor similarities to other accountability frameworks but unique in its specific focus on blockchain-anchored legal evidence and the four-primitive accountability model

Single revision with no indication of working group adoption or broader community engagement in AI accountability standards

Core AI agent topic addressing critical accountability and legal responsibility challenges that are fundamental to AI agent deployment

AI safety/alignment
Policy/governance
Human-agent interaction


This draft defines a cryptographic trust model for agent-to-agent interactions using PKI and OAuth patterns to establish verifiable identities, spawn chains, and cross-organizational authorization. It applies existing security primitives to the specific problem of agent provenance in multi-agent AI systems.

Useful contribution applying established PKI/OAuth patterns to agent trust - not novel cryptographically but addresses a real emerging need

Defines clear protocol mechanisms with CA templates and dual-signature policies, but lacks detailed examples and implementation specifics

While identity and trust are common themes, the specific A2A spawn chain and template approach has minor similarities to existing work

Single revision from 2026 with no evidence of working group activity or community engagement yet

Directly addresses core AI agent infrastructure - identity, trust, and provenance are fundamental for multi-agent systems

Agent identity/auth
A2A protocols
Policy/governance


This draft proposes an intent-based management framework for Software-Defined Vehicles (SDVs) to enable autonomous vehicle communication and coordination in intelligent transportation systems. The framework aims to simplify network, security, and application configuration in SDVs through high-level intent specifications rather than low-level device configuration.

Incremental application of well-established intent-based networking concepts to the automotive domain, without significant technical innovation beyond domain adaptation

Early architectural sketch with high-level framework description but lacks detailed protocol specifications, implementation details, or concrete examples

Significant conceptual overlap with existing intent-based networking frameworks and SDN management approaches, primarily distinguished by automotive use case focus

Appears to be single revision with no indication of working group adoption or broader community engagement in IETF context

Partially relevant as SDVs involve autonomous agents requiring coordination, but focuses more on network management infrastructure than core AI agent behaviors


```json
{
  "s": "This draft defines an authorization profile for OAuth 2.0 specifically designed for autonomous AI agents, extending existing standards with structured claims for agent identity, task context, and oversight requirements. It focuses on enabling context-aware, auditable authorization in agent-to-API scenarios without introducing new protocols.",
  "n": 4,
  "nn": "Notable originality in adapting OAuth 2.0 for autonomous agents with structured claims for delegation chains and human oversight - addresses genuinely new challenges",
  "m": 4,
  "mn": "At 83 pages, appears to be a detailed specification with comprehensive coverage of agent authorization scenarios and structured claims validation",
  "o": 2,
  "on": "While building on OAuth 2.0 and JWT, the agent-specific extensions and context-aware authorization mechanisms represent a fairly unique approach",
  "mo": 3,
  "mon": "Recent draft (2026-02-07) suggesting active development, though momentum level unclear without revision history",
  "r": 5,
  "rn": "Core AI agent topic - directly addresses critical need for agent identity, authorization, and oversight in autonomous systems",
  "c": ["Agent identity/auth", "AI safety/alignment", "Policy/governance"]
}
```


Proposes Agent Quality Graph (AQG) protocol for evaluating AI agent trustworthiness through delegation transaction graphs, similar to PageRank for web pages. Defines delegation record formats, graph construction, scoring algorithms, and query APIs for trust scores.

Notable adaptation of PageRank-style algorithms to agent trustworthiness - creative cross-domain application

Defines core protocol components and algorithms but lacks detailed implementation specifics

Some conceptual overlap with reputation systems but unique application to agent delegation graphs

Single revision with future date suggests early stage work

Directly addresses core challenge of agent trustworthiness evaluation in multi-agent systems

A2A protocols
AI safety/alignment
Agent identity/auth


This draft specifies multimodal requirements for agent-to-agent protocols, enabling autonomous agents to negotiate heterogeneous data capabilities and exchange synchronized content across text, file, audio/video, and sensor streams. It focuses on multi-channel communication sessions with adaptive QoS policies for diverse data types.

Useful contribution addressing multimodal agent communication, though builds on established multimedia protocol concepts

Early sketch stage - appears to be requirements document without detailed protocol mechanisms or implementation details

Shares concepts with existing multimedia protocols like WebRTC and SIP, but applies them specifically to autonomous agent communication

Single revision with recent publication date, no evidence of working group adoption or community engagement yet

Core AI agent topic directly addressing autonomous agent communication protocols and multimodal data exchange


Defines a comprehensive framework for AI agents to collaborate across different administrative domains and networks. Addresses identity federation, trust establishment, policy harmonization, and secure communication for cross-domain AI agent interoperability.

Notable originality in addressing cross-domain AI agent collaboration challenges with federated approach

Defines clear protocol mechanisms and framework components but lacks detailed implementation specifics

Some conceptual overlap with general federation protocols but unique focus on AI agent collaboration

Single revision draft with no clear working group adoption yet

Core AI agent topic addressing fundamental interoperability challenges for multi-domain collaboration

A2A protocols
Agent identity/auth
Policy/governance
Agent discovery/reg


This draft proposes a well-known URI (/.well-known/awp.json) and link relation to expose machine-readable descriptions of website workflows, enabling automated agents to interact predictably without web scraping. The format uses minimal JSON to describe states, actions, and events for common website operations.

Notable originality in creating a standardized way for websites to expose workflow metadata specifically for agent consumption, moving beyond traditional API approaches

Defines the protocol mechanism and JSON format but lacks detailed implementation examples and comprehensive specification of workflow description schemas

Some conceptual similarity to web discovery mechanisms like robots.txt or OpenAPI, but unique focus on workflow state machines for agents

Appears to be early-stage individual submission without clear working group adoption or broader community engagement

Directly addresses core challenge of agent-web interaction by providing structured alternative to web scraping, highly relevant to autonomous agent operations


This IETF draft proposes an in-band method for DNS operators to publish authenticated DNSSEC key parameters, enabling automatic bootstrapping of DNSSEC without out-of-band validation. The mechanism allows parent registries to cryptographically validate CDS/CDNSKEY records even when DS records are absent.

Addresses real DNSSEC deployment friction with a useful cryptographic validation approach, though builds incrementally on existing CDS/CDNSKEY mechanisms

Well-developed specification with clear protocol mechanics, validation procedures, and security considerations, approaching implementation-ready status

Shares core concepts with RFC 8078 and RFC 7344 on DNSSEC automation, but proposes a distinct in-band validation approach

IETF working group draft with active GitHub collaboration and clear preference establishment over existing methods indicates strong momentum

Pure DNS infrastructure protocol focused on DNSSEC bootstrapping with no AI or agent-related functionality


This draft defines an OAuth 2.1 extension for AI agents to obtain access tokens using PII collected through natural language conversations over channels like phone/text that don't support traditional OAuth flows. The protocol aims to prevent LLM hallucinations from causing impersonation attacks while enabling agent-based API access.

Novel approach to OAuth for conversational AI agents using PII-based authentication over non-web channels, addressing unique security challenges of LLM-powered systems

Single revision with future date suggests early development stage, no evidence of working group adoption or broader community engagement

Minor similarities to existing OAuth extensions but addresses unique problem space of conversational AI agents with distinct security considerations

Directly addresses core AI agent authentication challenges, specifically targeting LLM-powered systems and their unique security vulnerabilities

Agent identity/auth
AI safety/alignment
Human-agent interaction


This draft proposes architectural principles for integrating AI agents as first-class entities at each layer of the IP protocol stack while maintaining deterministic protocol layering for interoperability. The approach introduces agent controllers to coordinate AI agents across layers using agentic methods, aiming to evolve from static automation toward goal-driven closed-loop network operations.

Notable originality in proposing systematic agentic augmentation of existing protocol layers rather than replacing them, with coordinated multi-layer AI agent architecture

Single revision draft from research group, appears to be initiating discussion rather than building on established community work

Minor similarities to general autonomous networking concepts but unique in its specific agentic augmentation approach to protocol stack layers

Core AI agent topic directly addressing autonomous network operations with agentic AI systems including planning, reasoning, and tool invocation

Autonomous netops
A2A protocols
Policy/governance


This draft defines standardized benchmarking terminology for Ethernet-based network fabrics used in distributed AI training and inference workloads. It consolidates and extends existing RFC terminology with AI-specific definitions for collective communication primitives, RDMA transports, and performance metrics.

Incremental work extending existing benchmarking terminology to AI fabric context, useful but not groundbreaking

Well-structured terminology document with detailed definitions, examples, and clear scope as companion to methodology drafts

Explicitly builds on RFC 1242 and RFC 8238, shares concepts with networking benchmarking work but AI fabric focus is distinct

Active development as part of coordinated draft series, but limited evidence of broader WG momentum

Directly relevant to AI infrastructure with focus on distributed training/inference networking, essential foundation work


This draft outlines requirements for high-performance wide area networks to support big data and intelligent computing applications that require massive data transmission between data centers. The focus is on ensuring data integrity and providing stable, efficient transmission services in WANs and MANs.

Incremental work identifying network requirements for data-intensive applications - useful but not particularly novel

Early requirements document without detailed technical mechanisms or protocols defined

Shares networking optimization concepts with existing WAN and data center interconnect work

Single revision with basic requirements gathering, no clear working group traction yet

Tangentially related to AI through mention of intelligent computing applications, but primarily focused on general network performance requirements


This draft defines a simple format for content creators to express preferences about how automated systems should consume their content. It updates RFC 9309 and defines an HTTP header field for conveying these usage preference strings.

Incremental work building on existing preference mechanisms, but addresses emerging AI content consumption concerns

Detailed specification with clear syntax definitions, HTTP header field specification, and practical examples

Shares conceptual space with existing preference frameworks like RFC 7240, but focuses specifically on automated content consumption

Single revision with no clear working group adoption or broader community engagement yet

Directly addresses the timely issue of how content creators can signal preferences to AI systems and automated processors

Policy/governance
Data formats/interop
Human-agent interaction


```json
{
  "s": "Defines the 'mcp' URI scheme and discovery mechanisms for AI agents to find MCP servers via well-known URIs and DNS TXT records. Includes manifest integrity using JWS and security capability negotiation for trust establishment.",
  "n": 3,
  "nn": "Useful contribution applying standard web discovery patterns to MCP - not groundbreaking but addresses real need",
  "m": 4,
  "mn": "Detailed specification with clear URI scheme definition, dual discovery modes, JWS integrity, and security negotiation mechanisms",
  "o": 2,
  "on": "Minor similarities to general service discovery drafts but MCP-specific application is unique",
  "mo": 2,
  "mon": "Single revision with future date suggests early stage, unclear community adoption or working group interest",
  "r": 5,
  "rn": "Core AI agent topic - directly addresses agent-to-service discovery for Model Context Protocol integration",
  "c": ["Agent discovery/reg", "Agent identity/auth", "A2A protocols"]
}
```


This draft defines a vocabulary for expressing preferences about how digital assets should be used by automated processing systems, allowing content creators to declare restrictions or permissions for AI systems. It addresses the growing need for machine-readable policies governing AI training and usage of copyrighted or sensitive content.

Useful contribution addressing current AI governance needs, though vocabulary-based approaches for usage rights are somewhat established in other domains

Appears to be a detailed specification with defined vocabulary terms and likely includes examples of usage patterns

Shares conceptual ground with existing rights expression languages and content licensing frameworks, but focuses specifically on AI usage scenarios

Strong working group adoption indicated by draft-ietf prefix and addresses urgent industry need for AI content usage policies

Core AI governance topic addressing fundamental questions about training data rights and automated system permissions


This draft proposes incorporating security factors into routing decisions beyond traditional shortest-path metrics. The goal is to enable secure routing paths by considering the trustworthiness of links and forwarding nodes during route computation.

Incremental concept building on existing secure routing research, though application to modern networks has some merit

Only presents problem statement and high-level use cases without defining actual mechanisms or protocols

Significant overlap with decades of secure routing research including BGPsec, S-BGP, and trust-aware routing proposals

Appears to be single revision with basic problem statement, no evident working group interest or community engagement

This is about network routing security, not AI or autonomous agents - completely outside the AI/agent domain


This draft describes the SSH Agent Protocol for securely managing SSH private keys through a key agent service. It defines message formats and procedures for key operations like signing, key listing, and key management in SSH authentication workflows.

This is documentation of an existing, well-established protocol that has been in use for decades, not a novel contribution

Comprehensive specification with detailed message formats, operation procedures, and implementation guidance

Unique documentation of SSH-specific key agent protocol with no overlap with other IETF drafts

Single revision with no apparent working group activity or community engagement

This is about SSH key management agents, not AI agents - completely unrelated to artificial intelligence


Proposes MACP protocol suite for multi-agent collaboration with Agent Management Centers, gateways, and capability-based discovery mechanisms. Defines architecture for secure agent onboarding, distributed synchronization, and cross-domain collaboration.

Useful contribution addressing multi-agent coordination challenges, though builds on established distributed systems and service discovery concepts

Defines protocol components and architectural entities with clear roles, but lacks detailed message formats and implementation specifics

Shares concepts with service discovery protocols and distributed coordination mechanisms, but applies them specifically to agent collaboration

Single revision with future date suggests early stage work without established community engagement

Core AI agent topic directly addressing multi-agent system coordination, discovery, and secure collaboration protocols

A2A protocols
Agent discovery/reg
Agent identity/auth


This draft proposes a vocabulary category for 'AI Substitutive Use' that allows parties to express preferences about how their digital assets are used by AI systems, specifically focusing on inference-time uses that might generate outputs substituting for original content. It's designed to nest within a broader Automated Processing category from existing work.

incremental extension of existing AI preference vocabulary work with specific focus on substitutive use cases

early sketch phase with basic category definition but lacks detailed specification or implementation guidance

significant overlap with referenced AIPREF-VOCAB draft and builds directly on automated processing concepts

active development as evidenced by recent March 2026 date and references to July 2025 working group draft

directly relevant to AI governance and policy expression for content usage by AI systems


This draft analyzes security limitations in current Internet protocols (TLS, HTTP, MQTT) when applied to multi-agent systems, focusing on agent-specific requirements like dynamic identity and intermediary trust. It serves as a gap analysis to inform future IETF standardization for agent-native communication security.

Useful contribution applying established security analysis to the emerging domain of multi-agent systems, identifying specific gaps in current protocols for agent semantics

Early-stage analysis document that identifies problems and gaps but doesn't propose concrete solutions or protocols

While security analysis is common, the specific focus on multi-agent system communication patterns and agent-native semantics has minimal overlap with existing work

Single revision with recent publication date but no indication of working group adoption or broader community engagement yet

Directly addresses core AI agent communication security, covering fundamental protocols and frameworks used in multi-agent deployments


This draft specifies IAIP, a protocol for AI agent interconnection at gateway level using semantic intent rather than static addressing. It defines mechanisms for agent registration, capability advertisement, intent resolution and routing decisions to enable dynamic agent discovery and task dispatching.

Intent-based semantic routing for AI agents represents a notable departure from traditional network addressing paradigms

Protocol mechanisms are defined with clear functional components but lacks detailed message formats and implementation specifics

While agent discovery exists elsewhere, the intent-based semantic routing approach at gateway level appears relatively unique

Single draft submission with no indication of working group activity or broader community engagement

Directly addresses core AI agent networking challenges with agent-to-agent communication protocol design


This draft specifies SCEP (Simple Certificate Enrollment Protocol), a PKI communication protocol using PKCS#7 and PKCS#10 over HTTP for certificate enrollment. SCEP was originally developed by VeriSign for Cisco and now has wide implementation support across client and CA systems.

This is standardization of an existing, well-established protocol rather than novel work

Appears to be a detailed specification of a mature protocol with 43 pages of content

SCEP is a well-known existing protocol with multiple existing implementations and likely previous standardization efforts

Single draft submission with no clear indication of working group adoption or broad IETF community engagement

This is a traditional PKI certificate enrollment protocol with no AI or agent-specific components


```json
{
  "s": "The Agent Directory Service (ADS) is a distributed directory service for storing and discovering AI agent metadata based on skills and capabilities. It uses interconnected distributed directories with a content-routing protocol to enable agent discovery for problem-solving applications.",
  "n": 3,
  "nn": "Applies well-established distributed directory concepts to AI agent discovery, which is a useful contribution to emerging agent ecosystems",
  "m": 4,
  "mn": "At 31 pages, likely contains detailed protocol specifications, data structures, and operational mechanisms for the distributed directory service",
  "o": 2,
  "on": "While directory services exist, applying them specifically to AI agent skill-based discovery appears to have minimal overlap with existing IETF work",
  "mo": 2,
  "mon": "Single draft submission without clear working group adoption or broader community engagement visible",
  "r": 5,
  "rn": "Directly addresses core AI agent infrastructure needs for discovery and registration in distributed agent systems",
  "c": ["Agent discovery/reg", "A2A protocols", "Data formats/interop"]
}
```


This draft specifies the Governance Audit Record (GAR) system for auditing agentic AI systems, defining five audit types, alert systems, and audit packages for regulatory inspection. GAR provides verifiable evidence that AI agent sessions comply with governance frameworks and can be proven to regulators.

Novel approach to AI governance auditing with comprehensive audit architecture including multiple record types and regulatory compliance focus

Defines clear audit architecture and record types but likely needs more implementation details and examples for full specification maturity

References related drafts in same series (IDP, HEM) but appears to address unique audit and governance verification aspects

Part of active draft series with consistent authorship and forward-looking 2026 date suggesting ongoing development

Directly addresses core AI agent governance and regulatory compliance challenges, essential for enterprise AI deployment


Defines cryptographic inference chains to prove AI models actually performed claimed computations, using ZKML proofs and TEE attestation. Part of a three-chain 'Truth Stack' covering delegation (WHO), content (WHAT), and computational (HOW) provenance for AI agents.

Novel application of ZKML and TEE attestation to AI computational provenance, creating verifiable inference chains - addresses a gap not covered by existing standards

Defines protocol mechanisms and integrates with OAuth tokens, but lacks implementation details and test vectors for production deployment

Complements related drafts in same series (actor-chain, intent-chain) but addresses distinct computational provenance problem with unique technical approach

Active development as part of coordinated multi-draft effort, but uncertain broader community adoption beyond the draft series authors

Directly addresses core AI agent governance challenge of proving computational integrity - essential for trustworthy autonomous systems

Policy/governance
Agent identity/auth
Model serving/inference


AERO specifies an automatic route optimization service for IP internetworking over overlay multilink networks, using IPv6 neighbor discovery for network admission and mobility management. The protocol targets mobile applications across air/land/sea/space domains including aviation and intelligent transportation systems.

Builds on existing IPv6 ND and overlay networking concepts but provides useful integration for mobility scenarios

Detailed 120-page specification with comprehensive protocol mechanisms and clear technical approach

Shares overlay networking concepts with other mobility and tunneling drafts but has distinct OMNI interface approach

Single author draft with limited apparent working group engagement or community discussion

This is a networking mobility protocol with no AI or agent-related content - appears to be a false positive


This draft proposes using LISP (Locator/ID Separation Protocol) as a network substrate for AI agent communication, addressing requirements like location transparency and seamless mobility. It outlines minimal extensions to LISP for context-aware mapping and AI agent-centric communication patterns.

Useful application of existing LISP to AI agents, though the core insight of using ID/locator separation for agent mobility is somewhat predictable

Early stage work with basic framework outlined but lacking detailed protocol specifications or implementation guidance

While LISP is well-established, its specific application to AI agent networking has limited overlap with existing drafts

Single revision from 2026 with no clear indication of working group interest or community uptake

Directly addresses AI agent networking requirements with concrete technical approach, highly relevant to distributed AI systems

A2A protocols
Agent discovery/reg
Autonomous netops


This draft defines six cryptographically verifiable actor-chain profiles for OAuth 2.0 Token Exchange to preserve and validate delegation paths across multi-hop service-to-service and agentic workflows. It extends RFC 8693 with standardized mechanisms for tracking actor chains while providing different privacy and auditability tradeoffs.

Notable contribution addressing a clear gap in OAuth 2.0 Token Exchange for multi-hop agentic workflows with novel cryptographic verification profiles

Detailed 97-page specification with six well-defined profiles, specific processing rules, and comprehensive coverage of delegation scenarios

Builds on RFC 8693 but addresses previously unspecified delegation-path validation with minimal overlap to existing OAuth extensions

Single draft revision but addresses emerging need for agentic workflow authentication with reasonable technical approach

Directly relevant to AI agent authentication and authorization, specifically targeting agentic workflows and service-to-service delegation chains


This draft extends the EDHOC protocol to provide post-quantum cryptography resistance by incorporating KEM-based authentication mechanisms. It defines signature-free authentication using NIST-standardized ML-KEM and supports hybrid scenarios mixing KEM-based and PQC signature authentication.

Useful contribution applying established PQC KEMs to EDHOC authentication, though building on known cryptographic primitives

Detailed specification with concrete protocol extensions, KEM integration mechanisms, and hybrid authentication scenarios

Minor overlap with general PQC protocol work but unique in its specific KEM-based authentication approach for EDHOC

Active development indicated by 2026 date and substantial 42-page length, though momentum unclear without revision history

Tangentially related to AI/agents only through general authentication mechanisms that could be used by agent systems


MARC defines a vendor-neutral profile for generative models and agents to disclose uncertainty and control metadata, separating capability assessment from answer confidence. It specifies a bounded action set including answering, clarification, retrieval, tool use, deliberation, abstention, and escalation to improve auditability and reduce silent failures.

Notable originality in separating pre-decision capability assessment from post-decision confidence and defining a bounded primary action set for agent behaviors

Defined protocol with clear separation of concerns and bounded action semantics, though lacking detailed implementation examples

Minor similarities to general API standards but unique approach to uncertainty disclosure and agent control semantics

Single revision with future date suggests early stage development without demonstrated community engagement

Core AI agent topic addressing fundamental issues of uncertainty communication, control, and interoperability in generative systems

AI safety/alignment
Data formats/interop
Human-agent interaction
Model serving/inference


SlimWire Protocol (SWP) defines a binary framing layer and envelope format for agent-to-agent messaging with profile-based extensibility. The spec includes conformance testing via golden vectors and requires authenticated confidential channels for security.

Useful binary messaging protocol specifically designed for agent communication with extensible profiles, though builds on established framing concepts

Detailed specification with defined envelope encoding (E1), security binding (S1), conformance classes, and golden vector test artifacts

While binary framing exists elsewhere, the agent-specific profile dispatch and conformance model represent a relatively unique approach

Single draft from 2026 with no visible working group adoption or community discussion yet

Core infrastructure protocol specifically designed for agent-to-agent communication with tool invocation mapping and agent task lifecycle support


This draft proposes a framework for AI agent communications on the Internet, identifying protocols needed for agent-to-agent and agent-to-resource interactions. It surveys existing work like MCP and A2A protocols while establishing requirements for potential IETF standardization in this emerging space.

Provides a useful framework for organizing AI agent protocol requirements, though the core concepts of agent communication are becoming well-established in the field

Early framework document that identifies problem space and surveys existing work but lacks concrete protocol definitions or detailed specifications

Shares conceptual overlap with MCP and A2A protocol work mentioned in the abstract, plus general agent communication frameworks in the broader AI community

Shows active development as a 2026 draft addressing timely AI agent standardization needs, though IETF momentum in this space is still building

Core AI agent topic directly addressing fundamental protocols needed for agent communication, interoperability, and Internet-scale deployment

A2A protocols
Agent discovery/reg
Data formats/interop
Human-agent interaction


This draft updates compliance requirements for the Certificate Management over CMS (CMC) enrollment protocol, obsoleting RFCs 5274 and 6402. It provides implementation guidance for creating compliant CMC systems without defining new ASN.1 structures or transport mechanisms.

Trivial update to existing certificate management compliance requirements with no novel technical contributions

Detailed compliance specification that appears implementation-ready, building on well-established CMC protocol foundations

Direct successor document that obsoletes two existing RFCs covering the same compliance requirements for CMC

Standard maintenance update showing active development but limited broader community engagement signals

Certificate management has tangential relevance to agent authentication but this compliance document doesn't address AI/agent-specific concerns


Proposes OAuth 2.0 scope aggregation to reduce authorization friction in multi-step AI agent workflows by collecting all required permissions upfront. Aims to minimize repeated user consent prompts when agents need to access multiple resources across a workflow.

Incremental extension of OAuth 2.0 for AI workflows - addresses a real problem but solution is relatively straightforward application of existing patterns

Defines a clear protocol mechanism for scope aggregation with workflow-aware authorization, though likely needs more implementation details

Shares concepts with OAuth extensions and AI agent authorization work, but specific focus on workflow scope aggregation is reasonably distinct

February 2026 draft suggests early stage work with limited revision history or demonstrated community engagement

Directly addresses authorization challenges for AI agents that execute multi-step workflows requiring diverse resource access permissions

Agent identity/auth
Human-agent interaction


This draft defines cBRSKI, a constrained version of BRSKI for secure zero-touch onboarding of IoT devices using CBOR-encoded vouchers instead of JSON and CoAPS instead of HTTPS. It adapts the existing BRSKI protocol for resource-constrained networks with limited throughput and frequent packet loss.

Incremental adaptation of existing BRSKI protocol for constrained environments, primarily involving format changes (JSON to CBOR) and transport substitutions (HTTPS to CoAPS)

Detailed specification with comprehensive protocol definition, clear examples, and implementation guidance across 93 pages

Significant overlap with RFC 8995 (BRSKI) and RFC 9148, as this is explicitly a constrained variant that reuses core concepts and mechanisms

Strong working group adoption as an IETF draft with clear update relationship to established RFCs, indicating active development and community support

Tangentially related to AI/agents - focuses on IoT device bootstrapping and authentication rather than AI agent systems, though secure device onboarding could support AI-enabled IoT deployments


This draft proposes requirements and use cases for AI Agent Communication Networks (ACN) in 6G systems, focusing on agent-to-agent communication as a new traffic type. It discusses 3GPP use cases and potential frameworks for enabling AI agents to communicate and collaborate across networks.

Incremental work applying existing networking concepts to AI agent communication without significant technical innovation

Early-stage document with high-level requirements and use cases but lacks concrete protocol definitions or technical mechanisms

Shares concepts with other 6G and AI agent networking proposals, moderate overlap with existing mobile network research

Active development indicated by version 6, appears to have ongoing work but unclear community adoption

Directly addresses AI agent networking requirements with specific focus on agent-to-agent communication protocols


This draft specifies how nonces are provided by Registration/Certification Authorities to end entities for inclusion in attestation evidence within Certificate Signing Requests for CMP and EST protocols. It addresses freshness requirements for remote attestation in PKI certificate management scenarios.

Incremental extension applying existing nonce-based freshness concepts to CMP/EST certificate management protocols

Defines specific protocol mechanisms for nonce handling in CSRs with clear technical approach

Shares concepts with existing attestation and PKI management specifications but addresses specific gap

Single revision draft with limited visible community engagement or working group adoption

Tangentially related through attestation mechanisms but primarily focused on PKI certificate management rather than AI agents


This draft proposes best practices for web crawlers, focusing on responsible crawling behavior and server interaction guidelines. While crawler behavior is relevant to AI agents that scrape web content, this appears to be a general web crawling guidance document rather than AI-specific protocol work.

incremental contribution to existing crawler guidance

early sketch with limited technical detail provided

significant overlap with existing robots.txt and crawler standards

appears to be single author draft with limited activity

tangentially related - crawlers used by AI but not AI-specific


This draft defines a standardized metadata and query profile for discovering autonomous software agents, specifying JSON objects for publishing agent capabilities and enabling interoperable discovery services. The profile allows structured filtering and semantic matching while remaining agnostic to specific ML models or databases.

Useful contribution addressing a clear need for agent discovery standardization, though the approach of metadata profiles for service discovery follows established patterns

Detailed specification with comprehensive JSON schemas, examples, and clear protocol definitions that appear implementation-ready

While service discovery is well-established, the specific focus on autonomous agent capabilities and multi-modal matching criteria has minor similarities to existing work

Single revision with 2026 date suggests early stage without visible working group adoption or community engagement

Directly addresses core AI agent infrastructure needs for discovery and interoperability in multi-agent systems

Agent discovery/reg
Data formats/interop
A2A protocols


This draft presents a problem statement for zero trust standardization in IETF, arguing that while high-level architectural guidance exists (like NIST SP 800-207), the industry lacks interoperable frameworks and protocols for multi-vendor zero trust implementations. The document outlines use cases including cloud services, remote workforces, and intelligent agents, proposing IETF standardization work to enable zero trust interoperability.

Incremental contribution applying well-established zero trust concepts to IETF standardization context, with brief mention of intelligent agents but no novel technical insights

Pure problem statement document with numerous typos and grammatical errors, lacks any concrete protocol definitions or technical mechanisms

Significant overlap with existing zero trust architecture work (NIST SP 800-207) and various IETF security protocols, though focuses on interoperability gap

Single revision with future date (2026-05-06), no evidence of working group interest or community engagement

Only tangentially related to AI/agents through brief mention of 'intelligent agents' as a use case, primarily focused on general zero trust networking


Defines hybrid post-quantum key agreement methods for TLS 1.3 combining MLKEM with classical ECDHE. Specifies three concrete combinations: X25519MLKEM768, SecP256r1MLKEM768, and SecP384r1MLKEM1024.

Incremental work combining established post-quantum and classical cryptographic primitives in straightforward manner

Detailed specification with concrete parameter choices, wire formats, and implementation guidance

Significant overlap with other post-quantum TLS hybrid proposals and existing NIST standardization efforts

Strong industry momentum behind post-quantum cryptography adoption with active IETF working group development

Pure cryptographic protocol specification with no AI or agent-related functionality


AGIS defines a grammar-constrained interface language for LLM-based agents to interact with APIs using intent-expressing imperative verbs as method names. It serves as the native interface layer for the Agent Transfer Protocol (AGTP), similar to how HTML functions for HTTP.

Notable originality in defining grammar constraints for agent-API interactions with empirical validation showing 10-29 percentage point accuracy improvements over generic HTTP verbs

Detailed 50-page specification with YAML/JSON serialization formats, data manifest blocks, semantic declarations, and HTTP transport mapping

Minor similarities to existing API definition languages but unique focus on LLM agent consumption and grammar-constrained method naming

Single draft with no clear working group adoption or broader community engagement visible

Core AI agent topic addressing fundamental interface definition needs for LLM-based agents with empirical validation


This draft defines a standardized JSON format for automated HTTP clients (crawlers, AI bots) to publicly disclose their IP address ranges. The format aims to help website operators identify legitimate automated traffic and reduce inadvertent blocking of beneficial clients.

Incremental improvement on existing ad-hoc practices for IP range disclosure, providing standardization but no fundamental innovation

Well-defined specification with clear JSON schema, examples, and implementation guidance ready for deployment

Shares concepts with existing network management and traffic identification approaches, but specific to automated clients

Single revision draft with no clear working group adoption or community engagement signals

Directly addresses AI bot and automated agent traffic management, a growing operational concern for web infrastructure

ML traffic mgmt
Agent identity/auth
Data formats/interop


This draft proposes an experimental 'ai:' URI scheme to provide dedicated access points for AI resources, enabling native connectivity for autonomous systems while supporting human-facing applications through HTTPS gateways. The scheme aims to create a standardized way for AI systems and robots to discover and connect to AI resources across networks.

Useful contribution creating dedicated URI namespace for AI resources, though URI schemes for specialized domains have precedent

Early sketch with basic scheme definition but lacks detailed protocol mechanics, registration procedures, and security considerations

Minor similarities to existing URI schemes but AI-specific application is relatively unique

Single revision with future date suggests early stage without demonstrated community engagement

Directly relevant to AI agent infrastructure, addressing fundamental discovery and addressing needs for autonomous systems

A2A protocols
Agent discovery/reg
Data formats/interop


This draft proposes an AI agent architecture for Network Digital Twin (NDT) systems, integrating AI agents with digital twin technology for network management. The document appears to be an early conceptual framework for applying AI agents to digital representations of network infrastructure.

Useful contribution combining AI agents with network digital twins, though both concepts exist separately - the integration approach shows practical value

Early sketch stage with basic architecture outline, lacks detailed protocol specifications, implementation details, and concrete examples

Shares concepts with existing network management and digital twin drafts, but the specific AI agent integration angle provides some differentiation

Single revision draft with no clear working group adoption or community feedback visible yet

Directly relevant to AI agents in networking context, addressing autonomous network operations through digital twin technology


This draft specifies ELA (Lightweight Authorization using EDHOC), a protocol for authorizing enrollment of new devices in constrained networks using the EDHOC key exchange protocol. It enables zero-touch onboarding of devices leveraging trust anchors installed during manufacturing.

Incremental extension of existing EDHOC protocol for device authorization - useful but straightforward application

Detailed 44-page specification with clear protocol definitions and procedures for device enrollment

Shares device onboarding and authorization concepts with other IoT security drafts but focuses specifically on EDHOC integration

IETF working group draft with specific publication target date indicates active development and institutional support

Focuses on IoT device authorization rather than AI agents - only tangentially related through general authentication mechanisms


This draft proposes enhancing EAP-AKA' Forward Secrecy with Post-Quantum Key Encapsulation Mechanisms to protect against future quantum computer threats. It replaces the traditional ECDHE key exchange with quantum-resistant alternatives while maintaining the existing authentication framework.

Incremental upgrade replacing ECDHE with PQ-KEMs in existing EAP-AKA' FS protocol

Early specification stage at 15 pages, likely missing detailed protocol flows and implementation specifics

Significant conceptual overlap with general post-quantum cryptography migration efforts and other PQ-KEM integration drafts

Active development with recent July 2025 publication date, but uncertain working group status

Pure cryptographic protocol enhancement with no AI or agent-related content - appears to be false positive


This draft examines applying Zero Trust principles to network infrastructure, arguing that traditional perimeter-based security models are inadequate for modern distributed networks. It advocates for continuous verification of all network entities and communications regardless of location to prevent lateral movement and internal compromise.

Incremental application of well-established Zero Trust concepts to network infrastructure - useful but not particularly novel

Early conceptual document that examines problems and philosophy but lacks concrete protocols, mechanisms, or implementation details

Shares fundamental Zero Trust concepts with existing security frameworks and likely overlaps with other network security drafts

Single revision with no indication of working group adoption or broader community engagement

This is a traditional network security document about Zero Trust principles with no AI or agent-related content


This draft extends OAuth 2.0 to enable AI agents to securely obtain access tokens for acting on behalf of users through new requested_actor and actor_token parameters. It provides a framework for explicit user consent and delegation chains with enhanced auditability for AI agent authorization flows.

Useful contribution addressing AI agent delegation in OAuth, though builds incrementally on existing token delegation patterns

Detailed specification with clear protocol mechanics, parameter definitions, and flow descriptions approaching implementation readiness

Some conceptual similarity to token exchange and delegation flows but introduces AI-specific mechanisms not directly covered elsewhere

Single revision from February 2026 with no visible working group adoption or community discussion yet

Directly addresses core AI agent authentication and authorization challenges, highly relevant to AI agent ecosystem needs

Agent identity/auth
Human-agent interaction
Policy/governance


This draft extends TLS 1.3's key update mechanism to include fresh Diffie-Hellman exchanges within active sessions, providing post-compromise security that the current KeyUpdate mechanism lacks. The extension is designed for long-lived sessions in industrial IoT and telecommunications environments where static key compromise poses significant risks.

Useful contribution addressing a real limitation in TLS 1.3's forward secrecy guarantees for long-lived sessions

Detailed specification with protocol mechanisms defined, appears implementation-ready

Some conceptual similarity to existing key rotation mechanisms but addresses specific TLS 1.3 gap

IETF working group draft with clear security need and industry applications

This is a TLS security extension, not related to AI agents or artificial intelligence


This IETF draft provides considerations for configuring networks and systems to support distributed AI inference services, covering deployment from cloud to edge devices. It addresses factors for client connections to AI services and includes use cases like self-driving vehicles and network digital twins.

Incremental work applying existing networking concepts to AI deployment scenarios without introducing novel technical approaches

Early sketch stage - provides high-level considerations and use cases but lacks detailed protocols, mechanisms, or implementation specifics

Significant overlap with existing edge computing, distributed systems, and AI infrastructure deployment literature and standards

Active development within IRTF NMRG context, though unclear level of broader community engagement beyond research group

Directly relevant to AI agent deployment infrastructure, addressing key networking considerations for distributed AI services

Model serving/inference
ML traffic mgmt
Autonomous netops


Defines a standardized /.well-known/ai endpoint for web services to expose machine-readable capability descriptions to AI agents. Creates a structured JSON format optimized for LLM token efficiency to enable programmatic service discovery without parsing human documentation.

Useful contribution applying well-known URI pattern to AI agent discovery - logical but not obvious extension

Single revision with no clear working group adoption or community feedback yet

Some conceptual overlap with OpenAPI/service discovery but distinct focus on AI agent consumption

Directly addresses core AI agent infrastructure need for automated service discovery and capability exposure


MCP-AX adapts the SNMP AgentX protocol architecture to enable hierarchical aggregation of Model Context Protocol (MCP) servers, allowing AI agents to access distributed tool namespaces across heterogeneous networks. The protocol provides recursive namespace delegation and capability-aware routing for composing tool collections from cloud services to embedded devices.

Notable originality in adapting proven SNMP aggregation patterns to the emerging MCP ecosystem, creating a novel hierarchical tool composition architecture

Detailed specification with clear master-subagent architecture, namespace delegation mechanisms, and transport bridging - appears implementation-ready

Some conceptual similarity to service mesh patterns but unique application to MCP tool aggregation with minimal direct overlap

Active development indicated by 2026 date and substantial 25-page specification, though community adoption unclear for emerging MCP ecosystem

Core AI agent topic addressing critical infrastructure needs for tool composition and namespace management in distributed AI systems


This draft outlines networking scenarios for AI agents in enterprise and home broadband networks, distinct from mobile and internet deployments. The document is largely speculative, based on assumptions about emerging agentic services in these network environments.

Incremental extension of agent networking concepts to enterprise/broadband contexts without significant technical innovation

Appears to be primarily a problem statement and scenario description without concrete protocols or mechanisms

Likely shares conceptual overlap with general agent networking drafts but focuses on specific deployment environments

Single revision of an early-stage draft with no clear working group adoption signals

Directly addresses AI agent networking scenarios, though limited to specific network deployment contexts

A2A protocols
Autonomous netops
Agent discovery/reg


This draft proposes a cross-domain trust and authentication framework for AI agent-to-agent communications, addressing identity verification, authorization, and delegation across different trust domains. The framework aims to be protocol-agnostic and provide a consistent baseline for existing and emerging AI agent protocols.

Notable originality in addressing the specific challenge of cross-domain trust for AI agents, which is emerging as protocols mature

Active development indicated by 2026 date, but momentum unclear without working group adoption information

Some conceptual overlap with general identity/auth frameworks, but the AI agent cross-domain focus appears relatively unique

Core AI agent topic directly addressing critical trust infrastructure needs for agent ecosystems

Agent identity/auth
A2A protocols
Policy/governance


Defines a third-party attestation mechanism for verifying telephone number ownership in messaging platforms, supporting secure enrollment in interoperable messaging systems. The approach extends to other Service Independent Identifiers in the MIMI framework for cross-platform identity verification.

Incremental work applying standard proof-of-possession concepts to messaging platform identity verification

Defined mechanism with clear protocol elements but lacks detailed implementation specifics and examples

Shares identity attestation concepts with existing work but addresses specific MIMI messaging interoperability context

Active individual draft with clear use case alignment to ongoing MIMI working group efforts

Not about AI or agents - focuses on human user identity verification for messaging platforms


This draft proposes a networking framework for AI agents in enterprise and broadband environments, defining core components and their interactions. The framework aims to enable agent-to-agent communication and coordination in network management scenarios.

Incremental work extending existing network management concepts to agent-based systems without significant architectural innovation

Early stage draft with basic framework outline but lacks detailed protocol specifications, implementation details, or concrete examples

Shares conceptual overlap with existing network management frameworks and some agent communication proposals, but focuses on specific enterprise/broadband domain

Single draft submission with no evidence of working group adoption or broader community engagement yet

Directly addresses AI agent networking which is highly relevant to current industry needs for autonomous network operations


This draft defines a YANG data model for hierarchical topology coordination between language models of different sizes (tiny, small, large) in distributed inference scenarios. It proposes a standards-based approach for orchestrating secure LM interactions across heterogeneous edge-to-cloud environments with request escalation and decentralized validation.

Notable originality in applying network topology modeling to distributed LM coordination with formal YANG specification

Defined protocol mechanism with hierarchical architecture but likely needs more implementation details

Minor similarities to distributed AI serving approaches but unique focus on hierarchical LM topology modeling

Single revision from 2026 with no visible community engagement yet

Core AI agent topic addressing distributed inference coordination between multiple language models

A2A protocols
Model serving/inference
Agent identity/auth
Data formats/interop


This document defines mechanisms for coordinating and discovering EDHOC application profiles, including a CBOR-based canonical representation for describing and distributing these profiles. It addresses the need for standardized ways to agree on EDHOC parameters that are currently negotiated out-of-band.

Incremental work that systematizes existing ad-hoc practices for EDHOC profile coordination

Detailed specification with CBOR schemas, discovery mechanisms, and concrete well-known profiles

Minor overlap with general service discovery work but addresses EDHOC-specific coordination needs

Active development with regular revisions but limited to specialized EDHOC community

Pure cryptographic protocol work for key exchange coordination, not related to AI or agents


Proposes a framework for AI agents deployed on network devices to communicate and collaborate across devices for tasks like network measurement and troubleshooting. Analyzes requirements for inter-agent communication protocols in networking contexts.

Useful contribution addressing the specific need for cross-device AI agent coordination in networking, though builds on established multi-agent communication concepts

Early stage work that appears to focus on framework definition and requirements analysis rather than detailed protocol specification

Minor overlap with general multi-agent systems work, but focuses specifically on network device deployment which is relatively unique

Single draft submission with no clear indication of working group adoption or broader community engagement

Directly addresses core AI agent networking challenges including cross-device communication, collaboration protocols, and agent coordination


Specifies the Sovereign Policy Token Transaction (SPT-Txn) Framework that extends IETF Transaction Tokens with Capability Acquisition Tokens for fine-grained, auditable authorization across trust boundaries. Designed for regulated financial infrastructure, AI agent systems, and cross-organizational transaction chains requiring cryptographic guarantees of human-origin authorization.

Notable originality in combining capability-based authorization with transaction tokens, cryptographic binding of human identity commitments across delegation chains, and offline verification without issuer interaction

Single revision from future date (2026-04-27) suggests early stage, no evidence of working group adoption or broader community engagement yet

Minor similarities to existing OAuth and transaction token work, but unique approach to capability binding and human-origin identity propagation in multi-hop scenarios

Core AI agent topic addressing critical authorization and policy enforcement needs for agentic systems operating across organizational boundaries with human oversight requirements

Agent identity/auth
Policy/governance
A2A protocols


This draft defines an experimental Agent Persistent State (APS) Profile to address storage requirements for autonomous agents that maintain durable state like user preferences, embeddings, and audit traces. It proposes a vendor-neutral storage service class with emphasis on compliance, cryptographic erasure capabilities, and integration with container orchestration systems.

Notable originality in recognizing and addressing the 'layer mismatch' between agent storage needs and current infrastructure, with novel focus on compliance-oriented storage including cryptographic erasure

Single revision draft with experimental status, no indication of working group adoption or broader community engagement yet

Minor similarities to general storage standards but unique in its agent-specific focus and compliance requirements

Core AI agent infrastructure topic addressing fundamental storage requirements for autonomous agents with persistent state

Data formats/interop
Agent identity/auth
Policy/governance


ATP defines a cryptographically verifiable DAG protocol for tracking agent transactions with tamper-evident signed causality chains. The protocol aims to provide accountability and auditable lineage across distributed agentic systems through lightweight, transport-independent mechanisms.

Notable application of DAG cryptographic verification specifically to agent transaction tracking - bridges blockchain concepts with AI agent accountability in a novel way

65 pages suggests detailed specification with comprehensive protocol definition, though implementation readiness unclear without test vectors mentioned

Some conceptual overlap with general cryptographic audit trails and blockchain structures, but specific application to agent transactions appears unique

Future date (2026) and lack of WG context suggests early individual submission without established community momentum

Directly addresses core challenges in agent systems - accountability, provenance, and verifiable history are fundamental concerns for AI agent deployment

A2A protocols
Agent identity/auth
AI safety/alignment


This document explores applying existing IETF YANG data models for Attachment Circuit and Traffic Engineering to support dynamic AI model placement at edge cloud sites. It maps a use case of optimal edge location selection for real-time AI inference from street cameras across network segments to evaluate model applicability.

Incremental application of existing YANG models to edge AI placement - useful but not particularly novel

Defines specific protocol application with concrete use case mapping, though lacks implementation details

Shares concepts with existing edge computing and network management work, moderate overlap expected

Single revision from October 2025, too recent to assess broader momentum

Directly relevant to AI agent infrastructure, focusing on network-aware AI model placement and service optimization

Model serving/inference
Autonomous netops
ML traffic mgmt


This draft proposes an integrated security framework for 5G networks that uses Intent-Based Networking to translate high-level security intents into enforceable policies via I2NSF architecture. The system distributes policy enforcement across network and application levels with adaptive response to dynamic edge conditions.

Incremental combination of existing technologies (I2NSF, IBN, 5G NEF) without novel algorithmic or architectural contributions

Early sketch level - describes framework components and interactions but lacks detailed protocol specifications or implementation details

Significant overlap with existing I2NSF work and intent-based security management approaches in SDN/NFV contexts

Single revision from NMRG with limited evidence of broader community engagement or implementation activity

Partially relevant through intent-based networking aspects, but primarily focused on 5G security rather than AI agents


This draft proposes integrating AI-based Network Management Agents (NMA) into ACTN optical networks to achieve higher autonomy levels. It extends the ACTN architecture with agent-based components for autonomous perception, decision-making, and execution in optical network operations.

Useful integration of AI agents into established ACTN framework, though applying AI to network management is well-explored territory

Early architectural sketch with high-level components and use cases, lacks detailed protocols and implementation specifics

Shares autonomous network concepts with other drafts but focuses specifically on optical networks and ACTN integration

Single revision from February 2026, no clear indication of working group adoption or community engagement

Directly addresses AI agent integration in network management with specific focus on autonomous operations and agent-based decision making


Defines Agentic State Transfer (AST), an HTTP profile for maintaining consistency across multiple representations of the same resource using semantic validators and optimistic concurrency control. Addresses the problem where ETags are representation-specific rather than reflecting the underlying logical state of a resource.

Notable originality in addressing representation-level vs. logical-state consistency in HTTP, with the concept of Canonical Resource State being a fresh approach to multi-representation synchronization

Single revision draft with no clear working group adoption or community discussion visible

Minor similarities to existing HTTP extension drafts but the specific focus on cross-representation state consistency is relatively unique

Directly relevant to AI agents which often need to interact with resources through multiple representations and require consistent state management for reliable operation


This draft proposes a five-layer framework (identity, authorization, attestation, evidence, trust) to address gaps in Internet protocols for autonomous AI agent authentication and authorization. It serves as an informational guide for future standards work rather than defining specific wire protocols.

Notable originality in systematically decomposing agent trust into distinct layers and identifying specific gaps between human-centric Internet protocols and autonomous agent requirements

Well-defined framework with clear layer separation and gap analysis, but remains at conceptual level without detailed protocol specifications or implementation guidance

Minor similarities to general identity/authentication work, but the autonomous agent focus and five-layer decomposition appear relatively unique

Single revision with future date suggests early stage work without established community engagement or working group adoption

Core AI agent topic directly addressing fundamental trust and identity challenges for autonomous systems operating on the Internet


The Cosmos Protocol defines a comprehensive badge-based identity and communication system with 8 foundational components including cryptographic identity, trust scoring, post-quantum encryption, and semantic messaging. It aims to enable trust-native communication without requiring blockchain infrastructure while supporting passwordless authentication and decentralized identity management.

Notable integration of badge-based identity with trust scoring, post-quantum encryption, and semantic messaging in a unified protocol avoiding blockchain dependencies

Abstract cuts off mid-sentence and appears to be early draft with undefined RFC references and incomplete component descriptions

Shares identity and authentication concepts with existing decentralized identity work, but badge-based approach and trust-native design represents distinct implementation

Single draft submission with no apparent working group adoption or community discussion visible

Directly relevant to AI agents through identity management, trust scoring, semantic messaging grammar, and agent compatibility features

Agent identity/auth
A2A protocols
Data formats/interop


Defines a trust scoring and identity verification protocol for autonomous AI agents conducting financial transactions, featuring five-dimension trust metrics, cryptographic identities, and spend limits. Complements existing secure messaging protocols to enable trustworthy AI agent payment ecosystems.

Notable originality in combining multi-dimensional trust scoring with behavioral anomaly detection specifically for AI agent financial transactions - addresses emerging needs not well covered by existing identity/payment standards

Detailed specification with concrete trust scoring dimensions, cryptographic identity mechanisms using ECDSA P-256, spend limit tiers, and public API definitions - appears implementation-ready

Minor similarities to general identity and payment protocols, but specific focus on AI agent trust scoring and behavioral analysis represents a distinct approach

Active development as part of broader AI agent protocol suite, but unclear level of community adoption or working group interest at this early stage

Core AI agent topic directly addressing critical trust and financial security needs for autonomous agent ecosystems - highly relevant to emerging AI agent economy

Agent identity/auth
A2A protocols
AI safety/alignment


This draft defines authentication mechanisms for the Virtual World Region Agent Protocol (VWRAP), establishing trust models for client applications to verify user credentials before granting control over virtual world agents and digital assets. It focuses on identity verification and capability granting in virtual world environments.

Incremental work applying standard authentication patterns to virtual world agents - not particularly novel but addresses a specific domain need

Detailed specification with clear protocol definitions, trust model descriptions, and sufficient technical depth for implementation

Shares authentication and identity concepts with existing IETF identity work, but specific to virtual world agent domain

VWRAP working group has limited recent activity, and virtual world standardization efforts have historically struggled with adoption

Directly relevant to agent identity and authentication, addressing how users authenticate to control virtual agents and their digital assets


This draft proposes AI Network Security Agents for routers that use machine learning and behavioral analysis to provide adaptive, automated security responses. It outlines four use cases: dynamic defense against unknown threats, ACL optimization, configuration security, and collaborative defense across network devices.

Incremental application of well-established AI/ML security concepts to network routing devices, without introducing novel technical approaches

Future-dated draft (2026) suggests this is speculative work with no current community activity or momentum

Significant overlap with existing AI-driven network security, autonomous network operations, and ML-based threat detection work in IETF and broader industry

Directly relevant as it focuses on AI agents for network security with autonomous decision-making capabilities

Autonomous netops
ML traffic mgmt
AI safety/alignment


This draft proposes applying the Application-aware Networking (APN) framework to Internet of Agents (IoA) scenarios, where AI agents from different platforms need to communicate with varying network requirements. It analyzes the necessity of providing fine-grained network services for AI agent interactions.

Incremental application of existing APN framework to AI agent scenarios - straightforward extension rather than novel approach

Early sketch at 11 pages analyzing necessity but likely lacking detailed protocol mechanisms or implementation specifics

Shares APN concepts with existing networking drafts and IoA concepts with other AI agent networking proposals

Future date (2026-05-05) suggests single early revision without established community traction yet

Directly addresses AI agent networking requirements and inter-agent communication challenges in IoA scenarios


This draft defines an agent_session extension for vCon (Virtualized Conversations) to capture autonomous AI agents' internal sessions including prompts, tool calls, reasoning traces, and file artifacts alongside human conversations. It leverages existing vCon infrastructure for identity management, lifecycle handling, and cryptographic signing without requiring new top-level fields.

Useful contribution that adapts existing conversation recording format for AI agent sessions, though the core concept of structured agent trace capture is somewhat expected

Detailed specification with clear data model, CDDL schema references, and concrete examples of how agent sessions map to vCon structures

Minor similarities to conversation recording formats but unique in its specific mapping of agent internals to vCon model

Active development with recent date and part of broader vCon ecosystem, though unclear if adopted by working group

Directly addresses core need for standardized AI agent session recording, tracing, and auditability in conversational AI systems

Data formats/interop
Human-agent interaction
Policy/governance


This draft proposes Integrated Sensing and Communications (ISAC) as a use case for Computing-Aware Traffic Steering (CATS), where wireless networks jointly optimize sensing and communication functions. The document aims to identify challenges and requirements for ISAC scenarios in autonomous systems, smart cities, and industrial automation.

Incremental application of existing CATS framework to ISAC domain without novel technical contributions

Early sketch that presents use case scenarios but lacks detailed protocol mechanisms or specifications

Shares conceptual overlap with other CATS use case documents and ISAC research literature

Part of active CATS working group development with recent publication date suggesting ongoing work

Partially relevant as it addresses autonomous systems and intelligent traffic steering but focuses more on wireless sensing than core AI agent protocols

ML traffic mgmt
Autonomous netops
Other AI/agent


This draft extends the Entity Attestation Token (EAT) RFC to support capability attestation for agentic AI systems, introducing new claims for asserting agent functional, reasoning, and operational capabilities. It aims to enable trustworthy verification of autonomous agent capabilities in decentralized environments.

Notable application of existing attestation framework to emerging agentic AI domain with specific capability-focused extensions

Recent draft from December 2025 but no indication of working group adoption or broader community engagement yet

Builds on established EAT RFC but applies it to relatively new agentic AI attestation domain with minimal existing overlap

Directly addresses core challenge of verifying and attesting capabilities of autonomous AI agents in decentralized systems

Agent identity/auth
AI safety/alignment
Data formats/interop


This draft proposes extending certificate enrollment protocols (SCEP/EST) for AI agent identity using two scalable models: Zero-Knowledge Proofs for private continuous attestation, and one-time host bootstrapping for trusted endorsement. The approach addresses performance bottlenecks of per-enrollment verification while maintaining high-assurance identity for agentic AI systems.

Notable approach combining ZKP with traditional PKI for AI agent identity, and the dual-model framework addressing both privacy and scalability is original

Single revision from December 2024, too early to assess broader community interest or working group adoption

Some conceptual overlap with general attestation and PKI work, but the specific AI agent focus and dual-model approach are fairly unique

Core AI agent topic directly addressing fundamental identity and authentication needs for autonomous AI systems at scale


Proposes integrating AI agents into Digital Twin Network (DTN) architecture to enable autonomous network management capabilities. Extends traditional DTN by adding AI agents at each component level for more intelligent and adaptive operations.

Incremental combination of existing AI agent concepts with digital twin networking - straightforward extension rather than novel approach

Early architectural sketch without detailed protocols, mechanisms, or implementation specifics

Significant overlap with existing digital twin networking and AI-driven network management literature

Single revision with limited evidence of community engagement or working group interest

Directly relevant to AI agents in networking context, focusing on autonomous network operations


This draft proposes enhancing CDN node selection by combining anycast routing with QUIC transport to enable dynamic route advertisement based on real-time load and application requirements. The solution allows clients to signal service needs and enables server-initiated redirection using QUIC connection migration for more intelligent CDN performance.

Incremental combination of existing technologies (anycast, BGP, QUIC) for CDN optimization - not particularly novel but useful integration

Early sketch level - abstract describes concepts but lacks detailed protocol mechanisms, message formats, or implementation specifics

Shares concepts with existing CDN optimization and anycast routing work, plus QUIC connection migration proposals, but specific combination appears distinct

Single draft submission with no apparent working group activity or broader community engagement visible

This is purely about CDN infrastructure optimization and network protocols - no AI or agent-related content despite the rating request