A Survey of AI Agent Protocols
Reference: Yang, Chai, Song, Qi, Wen, Li, Liao, Hu, Lin, Chang, Liu, Wen, Yu, Zhang (2025). arXiv:2504.16736. Source file: 2504.16736v2.pdf. URL
Summary
This survey offers the first comprehensive classification and analysis of emerging AI agent protocols for LLM-based agents. The authors propose a two-dimensional taxonomy: (object orientation) context-oriented vs inter-agent protocols, and (application scenario) general-purpose vs domain-specific, covering MCP, A2A, ANP, ACP, Agora, LMOS, agents.json, LOKA, PXP, CrowdES, and others.
The paper then evaluates these protocols across efficiency, scalability, security, reliability, extensibility, operability, and interoperability, and sketches a forward-looking agenda: protocols should evolve from static to adaptive, from rules to ecosystems, and from mere communication to collective intelligence infrastructure.
Key Ideas
- Two-dimensional taxonomy of agent protocols (object orientation x application scenario).
- MCP as a universal context-oriented protocol with Host/Client/Server/Resource roles.
- Inter-agent layer splits into general-purpose (A2A, ANP, AITP, ACP, Agora) and domain-specific (robot, human-computer, system).
- Evaluation across 7 axes; case studies of MCP, A2A, ANP, Agora.
- Next-generation protocols need adaptability, privacy preservation, group interaction.
Connections
- Model Context Protocol
- Agent-to-Agent Protocol
- Agent Network Protocol
- Agent Communication Languages
- LLM Agents
Conceptual Contribution
- Claim: The zoo of emerging LLM Agents protocols can be organised along two orthogonal axes (context-oriented vs inter-agent; general-purpose vs domain-specific), and evaluated on a shared seven-axis rubric.
- Mechanism: Builds a taxonomy, then systematically compares Model Context Protocol, Agent-to-Agent Protocol, Agent Network Protocol, ACP, Agora, LMOS, agents.json, LOKA, PXP, CrowdES against efficiency, scalability, security, reliability, extensibility, operability, interoperability, with case studies.
- Concepts introduced/used: Model Context Protocol, Agent-to-Agent Protocol, Agent Network Protocol, Agent Communication Languages, LLM Agents, Multi-Agent Systems, Interoperability, Agent Discovery
- Stance: survey
- Relates to: Shares its subject with Survey Of Agent Interoperability Protocols but takes a broader taxonomic view; its forward-looking “protocols as ecosystems” framing converges with Levels Of Social Orchestration and motivates coordination layers like Ripple Effect Protocol. Historical continuity with KQML and FIPA-ACL is implicit.