Pith. sign in

REVIEW 36 cited by

A survey of agent interoperability protocols: Model Context Protocol (MCP), Agent Communication Protocol (ACP), Agent-to-Agent Protocol (A2A), and Agent Network Protocol (ANP)

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2505.02279 v2 pith:ABSV2B4Q submitted 2025-05-04 cs.AI

A survey of agent interoperability protocols: Model Context Protocol (MCP), Agent Communication Protocol (ACP), Agent-to-Agent Protocol (A2A), and Agent Network Protocol (ANP)

classification cs.AI
keywords agentprotocolacrosscommunicationsecureprotocolsscalabledecentralized
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

Large language model powered autonomous agents demand robust, standardized protocols to integrate tools, share contextual data, and coordinate tasks across heterogeneous systems. Ad-hoc integrations are difficult to scale, secure, and generalize across domains. This survey examines four emerging agent communication protocols: Model Context Protocol (MCP), Agent Communication Protocol (ACP), Agent-to-Agent Protocol (A2A), and Agent Network Protocol (ANP), each addressing interoperability in deployment contexts. MCP provides a JSON-RPC client-server interface for secure tool invocation and typed data exchange. ACP defines a general-purpose communication protocol over RESTful HTTP, supporting MIME-typed multipart messages and synchronous and asynchronous interactions. Its lightweight and runtime-independent design enables scalable agent invocation, while features like session management, message routing, and integration with role-based and decentralized identifiers (DIDs). A2A enables peer-to-peer task delegation using capability-based Agent Cards, supporting secure and scalable collaboration across enterprise agent workflows. ANP supports open network agent discovery and secure collaboration using W3C decentralized identifiers DIDs and JSON-LD graphs. The protocols are compared across multiple dimensions, including interaction modes, discovery mechanisms, communication patterns, and security models. Based on the comparative analysis, a phased adoption roadmap is proposed: beginning with MCP for tool access, followed by ACP for structured, multimodal messaging session-aware interaction and both online and offline agent discovery across scalable, HTTP-based deployments A2A for collaborative task execution, and extending to ANP for decentralized agent marketplaces. This work provides a comprehensive foundation for designing secure, interoperable, and scalable ecosystems of LLM-powered agents.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 36 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Mesh Inference: A Formal Model of Collective Inference Without a Center

    cs.MA 2026-06 unverdicted novelty 8.0

    Mesh inference allows a network of agents to reach the centralized optimum through local relaxations of a coupled free energy using only admitted observations, with convergence guaranteed by M-matrix properties in the...

  2. From Privacy to Workflow Integrity: Communication-Graph Metadata in Autonomous Agent Interoperability

    cs.CR 2026-06 unverdicted novelty 7.0

    Communication-graph metadata in A2A protocols allows label-blind classifiers to recover task classes at 6x chance from passive observation including workflow openings, with only full privacy properties reducing recove...

  3. Model-Native Computing Architecture: Envisioning Future System Architecture Through the Lens of Computer Architecture

    cs.AI 2026-05 unverdicted novelty 7.0

    Proposes the Intelligent Computing Architecture (ICA) as a six-layer framework with dual probabilistic-deterministic planes and three Amdahl-style heuristics to unify design of LLM-based systems.

  4. Dissociative Identity: Language Model Agents Lack Grounding for Reputation Mechanisms

    cs.CY 2026-05 conditional novelty 7.0

    VLMs preserve linearly separable visual magnitudes and can compare them, yet collapse at symbolic mapping because visual and textual number spaces remain fractured and disjoint.

  5. Behind EvoMap: Characterizing a Self-Evolving Agent-to-Agent Collaboration Network

    cs.AI 2026-05 unverdicted novelty 7.0

    Empirical study of EvoMap shows 98% of assets never reused, scores driven by self-reported metadata, and 84% of assets using vacuous validation tests.

  6. Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems

    cs.AI 2026-05 unverdicted novelty 7.0

    A survey that unifies prior work on multi-agent LLM systems via the LIFE framework, mapping dependencies across collaboration, failure attribution, and autonomous self-evolution while identifying cross-stage challenges.

  7. From Skills to Talent: Organising Heterogeneous Agents as a Real-World Company

    cs.AI 2026-04 unverdicted novelty 7.0

    OMC framework turns multi-agent AI into self-organizing companies with Talents, Talent Market, and E²R search, achieving 84.67% success on PRDBench (15.48 points above prior art).

  8. MPAC: A Multi-Principal Agent Coordination Protocol for Interoperable Multi-Agent Collaboration

    cs.MA 2026-04 accept novelty 7.0

    MPAC defines a multi-principal agent coordination protocol across Session, Intent, Operation, Conflict, and Governance layers, with 21 message types and state machines, delivering 95% lower coordination overhead in a ...

  9. From Component Manipulation to System Compromise: Understanding and Detecting Malicious MCP Servers

    cs.CR 2026-04 unverdicted novelty 7.0

    Presents a component-centric PoC dataset of malicious MCP servers and a two-stage behavioral deviation detector Connor achieving 94.6% F1-score.

  10. Faithful, Not Corrective: Message-Format Effects in Multi-Hop Agent Relays Are Tier-Dependent

    cs.AI 2026-06 conditional novelty 6.5

    Format effects on multi-hop LLM relay fidelity are tier-dependent: strong relays are nearly lossless, weak relays pay an encoding toll that fixed-key JSON later resists, and structure localizes rather than corrects errors.

  11. Data Facts: A Metadata Schema for Structured Data Exchange in the NANDini Multi-Agent Ecosystem

    cs.CR 2026-06 unverdicted novelty 6.0

    Data Facts is a lightweight JSON schema with security features enabling structured data exchange among autonomous agents, shown in evaluations to yield 100% decision accuracy and block all forgery attempts.

  12. LAP: An Agent-to-Instrument Protocol for Autonomous Science

    cs.AI 2026-06 unverdicted novelty 6.0

    LAP is a new protocol extending A2A and MCP with four physical-world primitives for agent-to-instrument interaction in autonomous laboratories.

  13. Dissociative Identity: Language Model Agents Lack Grounding for Reputation Mechanisms

    cs.CY 2026-05 unverdicted novelty 6.0

    LM agents' changeable modules prevent persistent identity and sanction sensitivity, making reputation mechanisms structurally inapplicable and requiring protocol-based behavioral harnesses instead.

  14. GRAIL: A Deep-Granularity Hybrid Resonance Framework for Real-Time Agent Discovery via SLM-Enhanced Indexing

    cs.AI 2026-05 unverdicted novelty 6.0

    GRAIL achieves over 79 times lower latency than LLM-parsing baselines and higher Recall@10 than vector search by combining SLM-enhanced prediction, pseudo-document expansion, and MaxSim resonance on the new AgentTaxo-...

  15. CADMAS-CTX: Contextual Capability Calibration for Multi-Agent Delegation

    cs.AI 2026-04 unverdicted novelty 6.0

    CADMAS-CTX replaces static skill profiles with context-conditioned Beta posteriors and uncertainty-penalized routing, yielding higher accuracy on GAIA (0.442) and SWE-bench (31.4%) than static baselines.

  16. Modality-Native Routing in Agent-to-Agent Networks: A Multimodal A2A Protocol Extension

    cs.AI 2026-04 unverdicted novelty 6.0

    Modality-native routing in A2A networks raises task accuracy from 32% to 52% over text-bottleneck baselines on a 50-task benchmark, but only when paired with capable downstream reasoning.

  17. A Residual-Shell-Based Lower Bound for Ollivier-Ricci Curvature

    cs.LG 2026-04 unverdicted novelty 6.0

    A residual-shell construction yields a tighter, computationally cheap lower bound for Ollivier-Ricci curvature that works for both 1-hop and k-hop random walks.

  18. A Formal Security Framework for MCP-Based AI Agents: Threat Taxonomy, Verification Models, and Defense Mechanisms

    cs.CR 2026-04 unverdicted novelty 6.0

    MCPSHIELD offers a threat taxonomy of 23 attack vectors, a labeled transition system verification model, and a defense-in-depth architecture claiming 91% coverage for MCP-based AI agents.

  19. Combating Data Laundering in LLM Training

    cs.CR 2026-04 conditional novelty 6.0

    Data laundering collapses original-query memorization detectors; SDR recovers useful detection signals by synthesizing training-like rewrites of proprietary data via a goal-details search.

  20. Security Considerations for Multi-agent Systems

    cs.CR 2026-03 unverdicted novelty 6.0

    No existing AI security framework covers a majority of the 193 identified multi-agent system threats in any category, with OWASP Agentic Security Initiative achieving the highest overall coverage at 65.3%.

  21. Agentic IoT: Architectures, Applications, and Challenges Toward the Internet of Agents

    cs.AI 2026-07 conditional novelty 5.0

    Agentic IoT is formalized as a cognitive IoT paradigm that embeds LLM-driven agents with perception-reasoning-planning-action-learning loops into cyber-physical systems across the device-edge-fog-cloud continuum.

  22. Governance Gaps in Agent Interoperability Protocols: What MCP, A2A, and ACP Cannot Express

    cs.MA 2026-06 unverdicted novelty 5.0

    Gap analysis of MCP, A2A, ACP, ANP, and ERC-8004 shows none support the full set of membership, deliberation, voting, dissent, escalation, and audit primitives required for governed agent communities.

  23. Clarus: Coordinating Autonomous Research Agents toward Web-Scale Scientific Collaboration

    cs.AI 2026-06 unverdicted novelty 5.0

    Clarus is a four-layer collaboration infrastructure with a project-agent-resource model that reformulates research as an open, traceable, multi-participant process.

  24. A Technical Taxonomy of LLM Agent Communication Protocols

    cs.MA 2026-06 unverdicted novelty 5.0

    Creates a five-dimension taxonomy (counterparty, payload, interaction state, discovery mechanism, schema flexibility) from nine protocols and identifies architectural patterns plus convergence trends.

  25. Overlaying Governance: A Compositional Authorization Framework for Delegation and Scope in Agentic AI

    cs.AI 2026-06 unverdicted novelty 5.0

    Introduces a compositional governance framework defining delegation types, resource scope attenuation, and an overlay operator for agentic AI authorization policies.

  26. HarnessAPI: A Skill-First Framework for Unified Streaming APIs and MCP Tools

    cs.AI 2026-05 unverdicted novelty 5.0

    HarnessAPI derives streaming HTTP endpoints, OpenAPI UI, and MCP tools from a single handler.py plus Pydantic schemas, cutting framework boilerplate by 74%.

  27. Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems

    cs.AI 2026-05 conditional novelty 5.0

    The survey proposes the LIFE framework to unify fragmented research on collaboration, failure attribution, and self-evolution in LLM multi-agent systems into a progression toward self-organizing intelligence.

  28. A Prompt-Aware Structuring Framework for Reliable Reuse of AI-Generated Content in the Agentic Web

    cs.AI 2026-05 unverdicted novelty 5.0

    A framework structures AI-generated content with prompt-aware metadata and verifiable credentials to support reliable assessment and reuse by agents.

  29. A Residual-Shell-Based Lower Bound for Ollivier-Ricci Curvature

    cs.LG 2026-04 unverdicted novelty 5.0

    A residual-shell construction yields a tighter, still-efficient lower bound on Ollivier–Ricci curvature for 1-hop and k-hop random walks, with reported tens-of-times speedups.

  30. Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering

    cs.SE 2026-04 accept novelty 5.0

    LLM agent progress depends on externalizing cognitive functions into memory, skills, protocols, and harness engineering that coordinates them reliably.

  31. Security Threat Modeling for Emerging AI-Agent Protocols: A Comparative Analysis of MCP, A2A, Agora, and ANP

    cs.CR 2026-02 unverdicted novelty 5.0

    The paper identifies twelve protocol-level security risks across MCP, A2A, Agora, and ANP and quantifies wrong-provider tool execution risk in MCP via a measurement-driven case study on multi-server composition.

  32. Towards Multi-Agent Economies: Enhancing the A2A Protocol with Ledger-Anchored Identities and x402 Micropayments for AI Agents

    cs.MA 2025-07 unverdicted novelty 5.0

    Proposes a DLT-anchored architecture extending the A2A protocol with on-chain AgentCards and x402 micropayments to enable multi-agent economies.

  33. The Path to Self-Evolving Clinical Systems: Scaling Medical Agents from Assistance to Autonomy

    cs.AI 2026-07 conditional novelty 4.5

    Medical agents should be scaled mainly by richer clinical environments and self-evolution loops, not parameter growth alone, under a three-level autonomy taxonomy.

  34. DeltaMCP: Incremental Regeneration via Spec-Aware Transformation for MCP servers

    cs.SE 2026-05 unverdicted novelty 4.0

    DeltaMCP introduces specification-aware incremental regeneration to keep MCP servers synchronized with evolving OpenAPI specifications.

  35. Empirical Comparison of Agent Communication Protocols for Task Orchestration

    cs.AI 2026-03 unverdicted novelty 4.0

    This work provides an empirical comparison of tool integration, multi-agent delegation, and hybrid architectures for LLM task orchestration, measuring response time, context consumption, cost, error recovery, and impl...

  36. A Survey of Context Engineering for Large Language Models

    cs.CL 2025-07 accept novelty 4.0

    The survey organizes Context Engineering into retrieval, processing, management, and integrated systems like RAG and multi-agent setups while identifying an asymmetry where LLMs handle complex inputs well but struggle...