A2A Protocol MCP Server

Bridge between MCP (Model Context Protocol) and Google's Agent2Agent (A2A) Protocol — enabling agent discovery, task delegation, and inter-agent communication.

What is A2A?

The Agent2Agent Protocol was introduced by Google in April 2025 as an open standard for AI agents to communicate with each other. It is now being standardized under the Linux Foundation to ensure vendor-neutral governance.

Key concepts:

• Agent Cards — JSON descriptors that advertise an agent's capabilities, skills, and endpoint
• Task lifecycle — Structured task delegation with states (submitted, working, completed, failed)
• Discovery — Agents can find each other by capability

How This Server Bridges MCP and A2A

MCP provides the interface between AI models and tools. A2A provides the interface between agents. This server combines both:

• MCP tools expose A2A operations to any MCP-compatible AI agent
• Agents can register themselves, discover other agents, and delegate tasks
• Local registry at ~/.a2a-agents/ stores Agent Cards and tasks

Tools

Tool	Description
create_agent_card	Create an A2A-compatible Agent Card with skills and endpoint
register_agent	Register an agent in the local A2A directory
discover_agents	Search for agents by capability
send_task	Create a task request following A2A protocol format
get_task_status	Check status of a delegated task
list_registered_agents	List all registered agents with capabilities

Installation

pip install a2a-protocol-mcp-server

Or with uvx:

uvx a2a-protocol-mcp-server

Configuration

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "a2a-protocol": {
      "command": "uvx",
      "args": ["a2a-protocol-mcp-server"]
    }
  }
}

Cursor / Windsurf

{
  "mcpServers": {
    "a2a-protocol": {
      "command": "uvx",
      "args": ["a2a-protocol-mcp-server"]
    }
  }
}

Usage Example

1. Create an Agent Card for your agent:
   create_agent_card("MyBot", "Translates text", ["translation", "german", "english"], "http://localhost:8000")

2. Register it:
   register_agent(<agent_card>)

3. Discover agents:
   discover_agents("translation")

4. Send a task:
   send_task("MyBot", "Translate 'Hello World' to German")

5. Check status:
   get_task_status("<task-id>")

Data Storage

Agent Cards and tasks are stored locally in ~/.a2a-agents/:

• agents.json — Registered Agent Cards
• tasks.json — Task history and status

Why A2A + MCP?

	MCP	A2A
Purpose	Model ↔ Tool interface	Agent ↔ Agent interface
Focus	Tool access, context	Discovery, delegation
Standard	Anthropic	Google → Linux Foundation

Together they create a complete agent communication stack: MCP handles the vertical (model-to-tools), A2A handles the horizontal (agent-to-agent).

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License

MIT