a2a-mcp

# A2A vs MCP Agent Demo This project demonstrates two different approaches to agent communication: 1. **Master Control Program (MCP)** - A centralized server-based approach where agents communicate through a central server 2. **Agent-to-Agent (A2A)** - A decentralized peer-to-peer approach where agents communicate directly with each other ## Installation 1. Create and activate a virtual environment: ```bash python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate ``` 2. Install dependencies: ```bash pip install -r requirements.txt ``` ## Usage ### MCP Server and Agents 1. Start the MCP server: ```bash python cli.py run-mcp-server ``` 2. In separate terminals, start one or more MCP agents: ```bash python cli.py run-mcp-agent --agent-id agent1 python cli.py run-mcp-agent --agent-id agent2 ``` The MCP server will track all connected agents and their status. You can view the status by opening http://localhost:5000 in your browser. ### A2A (Agent-to-Agent) Network 1. Start the first A2A agent: ```bash python cli.py run-a2a-agent --agent-id a2a1 --port 5001 ``` 2. Start additional A2A agents, connecting them to existing agents: ```bash python cli.py run-a2a-agent --agent-id a2a2 --port 5002 --peer localhost:5001 python cli.py run-a2a-agent --agent-id a2a3 --port 5003 --peer localhost:5001 --peer localhost:5002 ``` A2A agents will automatically discover other agents through their initial peers. You can type messages in any agent's terminal to broadcast them to all connected agents. ## Architecture ### MCP (Master Control Program) - Centralized server that tracks all agents - Agents register with the server and maintain connection through heartbeats - Server provides a web interface to monitor agent status - Simple and reliable but has a single point of failure ### A2A (Agent-to-Agent) - Decentralized peer-to-peer network - Agents connect directly to each other - Messages are flooded through the network - More resilient but requir…