Agent-to-Agent Model Context Protocol
STDIOEnables multi-agent collaboration for AI-powered development through real-time communication and coordination.
Enables multi-agent collaboration for AI-powered development through real-time communication and coordination.
A2AMCP brings Google's Agent-to-Agent (A2A) communication concepts to the Model Context Protocol (MCP) ecosystem, enabling AI agents to communicate, coordinate, and collaborate in real-time while working on parallel development tasks.
Originally created for SplitMind, A2AMCP solves the critical problem of isolated AI agents working on the same codebase without awareness of each other's changes.
✅ Server Status: WORKING! All 17 tools implemented and tested. Uses modern MCP SDK 1.9.3.
# Clone the repository git clone https://github.com/webdevtodayjason/A2AMCP cd A2AMCP # Start the server docker-compose up -d # Verify it's running docker ps | grep splitmind # Test the connection python verify_mcp.py
# Add the MCP server using Claude Code CLI claude mcp add splitmind-a2amcp \ -e REDIS_URL=redis://localhost:6379 \ -- docker exec -i splitmind-mcp-server python /app/mcp-server-redis.py
Add to your configuration file (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):
{ "mcpServers": { "splitmind-a2amcp": { "command": "docker", "args": ["exec", "-i", "splitmind-mcp-server", "python", "/app/mcp-server-redis.py"], "env": { "REDIS_URL": "redis://redis:6379" } } } }
When multiple AI agents work on the same codebase:
A2AMCP can coordinate any multi-agent scenario:
┌─────────────────┐
│ A2AMCP Server │ ← Persistent Redis-backed MCP server
│ (Port 5050) │ handling all agent communication
└────────┬────────┘
│ STDIO Protocol (MCP)
┌────┴────┬─────────┬─────────┐
▼ ▼ ▼ ▼
┌────────┐┌────────┐┌────────┐┌────────┐
│Agent 1 ││Agent 2 ││Agent 3 ││Agent N │
│Auth ││Profile ││API ││Frontend│
└────────┘└────────┘└────────┘└────────┘
@server.list_tools() and @server.call_tool() patternsservices: mcp-server: build: . container_name: splitmind-mcp-server ports: - "5050:5000" # Changed from 5000 to avoid conflicts environment: - REDIS_URL=redis://redis:6379 - LOG_LEVEL=INFO depends_on: redis: condition: service_healthy restart: unless-stopped redis: image: redis:7-alpine container_name: splitmind-redis ports: - "6379:6379" volumes: - redis-data:/data healthcheck: test: ["CMD", "redis-cli", "ping"] interval: 10s timeout: 5s retries: 5 volumes: redis-data: driver: local
pip install a2amcp-sdk
npm install @a2amcp/sdk
from a2amcp import A2AMCPClient, Project, Agent async def run_agent(): client = A2AMCPClient("localhost:5000") project = Project(client, "my-app") async with Agent(project, "001", "feature/auth", "Build authentication") as agent: # Agent automatically registers and maintains heartbeat # Coordinate file access async with agent.files.coordinate("src/models/user.ts") as file: # File is locked, safe to modify pass # File automatically released # Share interfaces await project.interfaces.register( agent.session_name, "User", "interface User { id: string; email: string; }" )
# Register agent register_agent("my-project", "task-001", "001", "feature/auth", "Building authentication") # Query another agent query_agent("my-project", "task-001", "task-002", "interface", "What's the User schema?") # Share interface register_interface("my-project", "task-001", "User", "interface User {...}")
See SDK Development Progress for details.
A2AMCP is designed to work with:
While inspired by Google's A2A protocol, A2AMCP makes specific design choices for AI code development:
| Feature | Google A2A | A2AMCP |
|---|---|---|
| Protocol | HTTP-based | MCP tools |
| State | Stateless | Redis persistence |
| Focus | Generic tasks | Code development |
| Deployment | Per-agent servers | Single shared server |
@server.list_tools(), @server.call_tool())mcp__splitmind-a2amcp__ toolsdocker ps | grep splitmindcurl http://localhost:5050/healthpython verify_mcp.py~/Library/Application Support/Claude/claude_desktop_config.json contains the A2AMCP server configurationWe welcome contributions! See CONTRIBUTING.md for guidelines.
# Clone repository git clone https://github.com/webdevtodayjason/A2AMCP cd A2AMCP # Install dependencies pip install -r requirements.txt # Run tests pytest # Start development server docker-compose -f docker-compose.dev.yml up
MIT License - see LICENSE file.
A2AMCP - Turning isolated AI agents into coordinated development teams