AI Agent Protocols Explained: MCP, A2A, ACP and More - YouTube
| 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, ACP, A2A, Oh my! — WorkOS Guides
MCP vs A2A vs ACP: AI Protocols Explained | Bluebash
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