AI: MCP, A2A, ACP Protocols

AI Agent Protocols Explained: MCP, A2A, ACP and More - YouTube

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Feature	MCP	A2A	ACP
Primary Purpose	Connects AI to tools and data sources	Connects AI agents to other AI agents	Enables local agent coordination
Initiated By	Anthropic	Google and partners	IBM/BeeAI
Best For	Tool discovery and data access	Multi-agent collaboration across platforms	Edge computing and local environments
Design Focus	Simplifying context access	Agent interoperability	Low-latency, offline operation
Security	Basic; evolved from hobbyist project	Enterprise-grade by design	Local sovereignty, no cloud dependency
Communication Style	Tool invocation	Two-way agent communication	Event-driven messaging
Network Requirements	Internet/cloud-based	Internet/cloud-based	Can operate offline
Ideal Environment	Enterprise cloud applications	Cross-platform agent ecosystems	Edge devices, robotics, IoT

An Unbiased Comparison of MCP, ACP, and A2A Protocols | by Sandi Besen | Medium

MCP, A2A, ACP: What does it all mean?

The Rise Of Agent Protocols: Exploring MCP, A2A And ACP | Blog - Everest Group

MCP, ACP, and A2A, Oh My! The Growing World of Inter-agent Communication | Camunda

MCP, ACP, A2A, Oh my! — WorkOS Guides

MCP vs A2A vs ACP: AI Protocols Explained | Bluebash

GitHub - Tsadoq/a2a-mcp-tutorial: A tutorial on how to use Model Context Protocol by Anthropic and Agent2Agent Protocol by Google

GitHub - GongRzhe/A2A-MCP-Server: A mcp server that bridges the Model Context Protocol (MCP) with the Agent-to-Agent (A2A) protocol, enabling MCP-compatible AI assistants (like Claude) to seamlessly interact with A2A agents.