A Technical Taxonomy of LLM Agent Communication Protocols

• URL: http://arxiv.org/abs/2606.19135v1
• Date: Wed, 17 Jun 2026 14:45:20 GMT
• Title: A Technical Taxonomy of LLM Agent Communication Protocols
• Abstract summary: This study develops a technical taxonomy to classify and analyze large language models (LLMs) agent communication protocols.<n>The framework guides protocol selection and highlights open research gaps such as privacy and policy enforcement.
• Score: 60.76747983053368
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: As 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. This study develops a technical taxonomy to classify and analyze LLM agent communication protocols. Following an established iterative method, we defined the taxonomy's purpose, meta-characteristic, and ending conditions, then performed five iterations, three empirical-to-conceptual and two conceptual-to-empirical, on nine actively maintained open-source protocols with demonstrable adoption. The taxonomy comprises five dimensions: counterparty, payload, interaction state, discovery mechanism, and schema flexibility. Classification reveals recurring architectural patterns: all sampled agent-to-agent protocols combine hybrid payloads with session-state persistence; most protocols support multiple predefined schemas, and two negotiate schemas at runtime, indicating a trend toward schema flexibility; decentralized discovery remains rare. 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. The framework guides protocol selection and highlights open research gaps such as privacy and policy enforcement.}

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