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webdevtodayjason/a2amcp

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A2AMCP is a Agent2Agent MCP communication Server taking the concept from Google's Agent2Agent Protocol (A2A)

Обзор

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. Add to your configuration file (~/Library/Application Support/Claude/claude_desktop_config.json on macOS): When multiple AI agents work on the same codebase: - : Agents create conflicting code, duplicate efforts, and cause merge conflicts - : Agents coordinate, share interfaces, prevent conflicts, and work as a team A2AMCP can coordinate any multi-agent scenario: - : Different agents building separate services - : Frontend and backend agents collaborating - : Multiple agents creating interconnected docs - : Test writers coordinating with feature developers - : Agents working on different...

README

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A2AMCP - Agent-to-Agent Model Context Protocol

Enabling Seamless Multi-Agent Collaboration for AI-Powered Development

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.

🚀 Quick Start

# 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

Configure Your Agents

Claude Code (CLI)

# 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

Claude Desktop

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"
      }
    }
  }
}

🎯 What Problem Does A2AMCP Solve?

When multiple AI agents work on the same codebase:

  • Without A2AMCP: Agents create conflicting code, duplicate efforts, and cause merge conflicts
  • With A2AMCP: Agents coordinate, share interfaces, prevent conflicts, and work as a team

Generic Use Cases Beyond SplitMind

A2AMCP can coordinate any multi-agent scenario:

  • Microservices: Different agents building separate services
  • Full-Stack Apps: Frontend and backend agents collaborating
  • Documentation: Multiple agents creating interconnected docs
  • Testing: Test writers coordinating with feature developers
  • Refactoring: Agents working on different modules simultaneously

🏗️ Architecture

┌─────────────────┐
│   A2AMCP Server │ ← Persistent Redis-backed MCP server
│   (Port 5050)   │   handling all agent communication
└────────┬────────┘
         │ STDIO Protocol (MCP)
    ┌────┴────┬─────────┬─────────┐
    ▼         ▼         ▼         ▼
Открыть полный README на GitHub

Установка

docker exec -i splitmind-mcp-server python /app/mcp-server-redis.py
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Конфигурация

{ "mcpServers": { "splitmind-a2amcp": { "command": "docker", "args": ["exec", "-i", "splitmind-mcp-server", "python", "/app/mcp-server-redis.py"], "env": { "REDIS_URL": "redis://redis:6379" } } } }