Which integrations are available for this server?

Used to build the web interface for monitoring agent status and tracking connected agents in the MCP server implementation Provides the core runtime environment for both the MCP server and agent implementations, supporting both centralized and peer-to-peer communication models

How do I use A2A MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@A2A MCP Server list all connected agents and their current status" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

A2A ⚡ MCP Agents

This project demonstrates two different approaches to agent communication:

Master Control Program (MCP) - A centralized server-based approach where agents communicate through a central server
Agent-to-Agent (A2A) - A decentralized peer-to-peer approach where agents communicate directly with each other

Installation

Create and activate a virtual environment:

python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate

Install dependencies:

pip install -r requirements.txt

Related MCP server: Playwright MCP Server

Usage

MCP Server and Agents

Start the MCP server:

python cli.py run-mcp-server

In separate terminals, start one or more MCP agents:

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

Start the first A2A agent:

python cli.py run-a2a-agent --agent-id a2a1 --port 5001

Start additional A2A agents, connecting them to existing agents:

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 requires more complex coordination
No single point of failure

Project Structure

a2a_mcp/ ├── agents/ # Agent implementations │ ├── mcp_agent.py # MCP-based agent │ └── a2a_agent.py # Peer-to-peer agent ├── mcp/ # MCP server implementation │ └── server.py # Flask-based MCP server ├── cli.py # Command-line interface └── requirements.txt # Python dependencies