A Technical Taxonomy of LLM Agent Communication Protocols: Classifying Multi-Agent System Interoperability
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[Submitted on 17 Jun 2026]
Summary
This study develops a technical taxonomy to classify and analyze LLM agent communication protocols. Using an established iterative method, the researchers analyzed nine actively maintained open-source protocols across five dimensions: counterparty, payload, interaction state, discovery mechanism, and schema flexibility. Key findings include that all sampled agent-to-agent protocols combine hybrid payloads with session-state persistence, most support multiple predefined schemas, and two negotiate schemas at runtime—indicating a trend toward schema flexibility. Decentralized discovery remains rare. The analysis suggests short-term convergence pressure toward unified protocols, but long-term evolution toward a federated, layered protocol stack rather than a single dominant protocol. The framework guides protocol selection and highlights open research gaps such as privacy and policy enforcement.
Source
Twitter / XA Technical Taxonomy of LLM Agent Communication Protocols: Classifying Multi-Agent System Interoperabilityarxiv.orgKey quotes
· 5 pulledAs large language models (LLMs) advance and multi-agent systems aim to overcome the limits of standalone agents, robust communication protocols are becoming essential infrastructure for distributed agent networks.
Nonetheless, the fragmented protocol landscape presents a significant interoperability challenge.
Classification reveals recurring architectural patterns: all sampled agent-to-agent protocols combine hybrid payloads with session-state persistence.
Analysis suggests short-term convergence pressure toward protocols unifying agent-to-agent and agent-to-context (tool and data) communication.
Long-term, however, no single protocol is likely to maximize versatility, efficiency, and portability simultaneously. The field will more likely evolve toward a federated, layered protocol stack.
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