# 多智能体通信协议五维分类法报告发布

- 来源：elvis (@omarsar0)
- 发布时间：2026-06-22 22:36
- AIHOT 分数：53
- AIHOT 链接：https://aihot.virxact.com/items/cmqpbl3z908olslx6ogmxkkqz
- 原文链接：https://x.com/omarsar0/status/2069066883995758814

## AI 摘要

该报告针对LLM多智能体系统的通信瓶颈，构建了五维分类法（对方、有效载荷、交互状态、发现机制、模式灵活性），系统梳理了9个积极维护的开源智能体协议，覆盖MCP和A2A的实际格局。报告发现两个突出模式：每个智能体间协议都采用混合有效载荷与会话状态持久化组合，而去中心化发现机制仍极为罕见。领域正悄然标准化有状态会话，但发现与策略执行层仍留白。该报告为今年选择通信层时提供了九大协议的真实对比参考。

## 正文

Great report on LLM agent communication protocols.

Communication is a huge bottleneck in multi-agent systems.

（worth bookmarking）

The report builds a five-dimensional taxonomy （counterparty， payload， interaction state， discovery mechanism， schema flexibility） across nine actively maintained open-source agent protocols， so it maps the real MCP and A2A landscape.

Two patterns stand out. Every agent-to-agent protocol sampled pairs of hybrid payloads with session-state persistence， and decentralized discovery is still rare. So the field is quietly standardizing on stateful sessions while leaving discovery and policy enforcement open.

Why does it matter？

If you are choosing a communication layer this year， this discusses what nine real protocols actually do.

Paper： https://arxiv.org/abs/2606.19135

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