{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:ABSV2B4Q6P4NWPS6TFDC6GDVJR","short_pith_number":"pith:ABSV2B4Q","schema_version":"1.0","canonical_sha256":"00655d0790f3f8db3e5e99462f18754c48299cf5c6ba5fe22d97e8a7724a8b28","source":{"kind":"arxiv","id":"2505.02279","version":2},"attestation_state":"computed","paper":{"title":"A survey of agent interoperability protocols: Model Context Protocol (MCP), Agent Communication Protocol (ACP), Agent-to-Agent Protocol (A2A), and Agent Network Protocol (ANP)","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Abul Ehtesham, Aditi Singh, Gaurav Kumar Gupta, Saket Kumar","submitted_at":"2025-05-04T22:18:27Z","abstract_excerpt":"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"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2505.02279","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-05-04T22:18:27Z","cross_cats_sorted":[],"title_canon_sha256":"eee176feb2fe8af2278df55bc4477990dd7e59ae2ee8a5b40e6ec88eccbacfab","abstract_canon_sha256":"1c51077ec62a02a24b02bd1d971c6e9344278a63173d9ac6fbd112302f80f457"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:08:19.979147Z","signature_b64":"vAgaDMC1d+4e8OA8TLPNE5ZkA6zrxLXehGD54GDSFYTnJRbMhmh/8Ja+MkeIGa13Mh9as+WyjzjmBmbsjWZHAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"00655d0790f3f8db3e5e99462f18754c48299cf5c6ba5fe22d97e8a7724a8b28","last_reissued_at":"2026-07-05T11:08:19.978668Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:08:19.978668Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A survey of agent interoperability protocols: Model Context Protocol (MCP), Agent Communication Protocol (ACP), Agent-to-Agent Protocol (A2A), and Agent Network Protocol (ANP)","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Abul Ehtesham, Aditi Singh, Gaurav Kumar Gupta, Saket Kumar","submitted_at":"2025-05-04T22:18:27Z","abstract_excerpt":"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"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.02279","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2505.02279/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2505.02279","created_at":"2026-07-05T11:08:19.978721+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.02279v2","created_at":"2026-07-05T11:08:19.978721+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.02279","created_at":"2026-07-05T11:08:19.978721+00:00"},{"alias_kind":"pith_short_12","alias_value":"ABSV2B4Q6P4N","created_at":"2026-07-05T11:08:19.978721+00:00"},{"alias_kind":"pith_short_16","alias_value":"ABSV2B4Q6P4NWPS6","created_at":"2026-07-05T11:08:19.978721+00:00"},{"alias_kind":"pith_short_8","alias_value":"ABSV2B4Q","created_at":"2026-07-05T11:08:19.978721+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":31,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.26211","citing_title":"Data Facts: A Metadata Schema for Structured Data Exchange in the NANDini Multi-Agent Ecosystem","ref_index":7,"is_internal_anchor":false},{"citing_arxiv_id":"2606.19537","citing_title":"Mesh Inference: A Formal Model of Collective Inference Without a Center","ref_index":34,"is_internal_anchor":false},{"citing_arxiv_id":"2606.19135","citing_title":"A Technical Taxonomy of LLM Agent Communication Protocols","ref_index":25,"is_internal_anchor":false},{"citing_arxiv_id":"2606.07150","citing_title":"From Privacy to Workflow Integrity: Communication-Graph Metadata in Autonomous Agent Interoperability","ref_index":14,"is_internal_anchor":false},{"citing_arxiv_id":"2606.03755","citing_title":"LAP: An Agent-to-Instrument Protocol for Autonomous Science","ref_index":11,"is_internal_anchor":false},{"citing_arxiv_id":"2606.03518","citing_title":"Overlaying Governance: A Compositional Authorization Framework for Delegation and Scope in Agentic AI","ref_index":10,"is_internal_anchor":false},{"citing_arxiv_id":"2606.00288","citing_title":"Model-Native Computing Architecture: Envisioning Future System Architecture Through the Lens of Computer Architecture","ref_index":44,"is_internal_anchor":false},{"citing_arxiv_id":"2606.31498","citing_title":"Governance Gaps in Agent Interoperability Protocols: What MCP, A2A, and ACP Cannot Express","ref_index":18,"is_internal_anchor":false},{"citing_arxiv_id":"2606.30246","citing_title":"Clarus: Coordinating Autonomous Research Agents toward Web-Scale Scientific Collaboration","ref_index":2,"is_internal_anchor":false},{"citing_arxiv_id":"2605.25815","citing_title":"Behind EvoMap: Characterizing a Self-Evolving Agent-to-Agent Collaboration Network","ref_index":9,"is_internal_anchor":false},{"citing_arxiv_id":"2605.28148","citing_title":"DeltaMCP: Incremental Regeneration via Spec-Aware Transformation for MCP servers","ref_index":9,"is_internal_anchor":false},{"citing_arxiv_id":"2605.30169","citing_title":"Dissociative Identity: Language Model Agents Lack Grounding for Reputation Mechanisms","ref_index":44,"is_internal_anchor":false},{"citing_arxiv_id":"2605.22733","citing_title":"HarnessAPI: A Skill-First Framework for Unified Streaming APIs and MCP Tools","ref_index":7,"is_internal_anchor":false},{"citing_arxiv_id":"2604.01905","citing_title":"From Component Manipulation to System Compromise: Understanding and Detecting Malicious MCP Servers","ref_index":15,"is_internal_anchor":false},{"citing_arxiv_id":"2605.14892","citing_title":"Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems","ref_index":241,"is_internal_anchor":false},{"citing_arxiv_id":"2507.19550","citing_title":"Towards Multi-Agent Economies: Enhancing the A2A Protocol with Ledger-Anchored Identities and x402 Micropayments for AI Agents","ref_index":5,"is_internal_anchor":false},{"citing_arxiv_id":"2602.11327","citing_title":"Security Threat Modeling for Emerging AI-Agent Protocols: A Comparative Analysis of MCP, A2A, Agora, and ANP","ref_index":8,"is_internal_anchor":false},{"citing_arxiv_id":"2603.09002","citing_title":"Security Considerations for Multi-agent Systems","ref_index":120,"is_internal_anchor":false},{"citing_arxiv_id":"2605.14892","citing_title":"Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems","ref_index":240,"is_internal_anchor":false},{"citing_arxiv_id":"2603.22823","citing_title":"Empirical Comparison of Agent Communication Protocols for Task Orchestration","ref_index":27,"is_internal_anchor":false},{"citing_arxiv_id":"2603.22823","citing_title":"Empirical Comparison of Agent Communication Protocols for Task Orchestration","ref_index":28,"is_internal_anchor":false},{"citing_arxiv_id":"2507.13334","citing_title":"A Survey of Context Engineering for Large Language Models","ref_index":257,"is_internal_anchor":false},{"citing_arxiv_id":"2605.09283","citing_title":"A Prompt-Aware Structuring Framework for Reliable Reuse of AI-Generated Content in the Agentic Web","ref_index":8,"is_internal_anchor":false},{"citing_arxiv_id":"2604.22446","citing_title":"From Skills to Talent: Organising Heterogeneous Agents as a Real-World Company","ref_index":31,"is_internal_anchor":false},{"citing_arxiv_id":"2604.12213","citing_title":"Modality-Native Routing in Agent-to-Agent Networks: A Multimodal A2A Protocol Extension","ref_index":4,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ABSV2B4Q6P4NWPS6TFDC6GDVJR","json":"https://pith.science/pith/ABSV2B4Q6P4NWPS6TFDC6GDVJR.json","graph_json":"https://pith.science/api/pith-number/ABSV2B4Q6P4NWPS6TFDC6GDVJR/graph.json","events_json":"https://pith.science/api/pith-number/ABSV2B4Q6P4NWPS6TFDC6GDVJR/events.json","paper":"https://pith.science/paper/ABSV2B4Q"},"agent_actions":{"view_html":"https://pith.science/pith/ABSV2B4Q6P4NWPS6TFDC6GDVJR","download_json":"https://pith.science/pith/ABSV2B4Q6P4NWPS6TFDC6GDVJR.json","view_paper":"https://pith.science/paper/ABSV2B4Q","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.02279&json=true","fetch_graph":"https://pith.science/api/pith-number/ABSV2B4Q6P4NWPS6TFDC6GDVJR/graph.json","fetch_events":"https://pith.science/api/pith-number/ABSV2B4Q6P4NWPS6TFDC6GDVJR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ABSV2B4Q6P4NWPS6TFDC6GDVJR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ABSV2B4Q6P4NWPS6TFDC6GDVJR/action/storage_attestation","attest_author":"https://pith.science/pith/ABSV2B4Q6P4NWPS6TFDC6GDVJR/action/author_attestation","sign_citation":"https://pith.science/pith/ABSV2B4Q6P4NWPS6TFDC6GDVJR/action/citation_signature","submit_replication":"https://pith.science/pith/ABSV2B4Q6P4NWPS6TFDC6GDVJR/action/replication_record"}},"created_at":"2026-07-05T11:08:19.978721+00:00","updated_at":"2026-07-05T11:08:19.978721+00:00"}