A2A Protocol: How AI Agents Talk to Each Other
The Agent-to-Agent (A2A) protocol is an open standard by Google for AI agents to discover, communicate, and collaborate across platforms and frameworks.
What is the A2A Protocol?
The Agent-to-Agent (A2A) protocol is an open standard introduced by Google that enables AI agents to discover each other's capabilities, communicate, and collaborate — regardless of which framework or platform they're built on.
A2A solves a critical problem: as organizations deploy multiple AI agents (from different vendors, built with different frameworks), these agents need a standard way to work together.
A2A vs MCP
MCP (Model Context Protocol) by Anthropic: Standardizes how LLMs connect to tools and data sources. Think of it as the USB port for AI tools.
A2A by Google: Standardizes how agents communicate with each other. Think of it as the HTTP for AI agents.
They're complementary: •MCP = agent ↔ tool communication •A2A = agent ↔ agent communication
A production system might use both: MCP to connect agents to databases and APIs, A2A to coordinate between agents.
How A2A Works
1. Agent Cards — each agent publishes a JSON description of its capabilities 2. Discovery — agents find each other via a registry or direct URL 3. Task delegation — one agent sends a task request to another 4. Streaming responses — the receiving agent streams results back 5. Artifact exchange — agents share structured data, files, or results
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Frequently Asked Questions
Is A2A the same as MCP?↓
No. MCP (Anthropic) is for connecting AI to tools/data. A2A (Google) is for agent-to-agent communication. They solve different problems and can be used together.
Should I use A2A or MCP?↓
Use MCP to give your agent access to tools and databases. Use A2A when you have multiple agents that need to collaborate. Most production systems will eventually use both.