Example A2A Agent

This repository implements a simple Agent-to-Agent (A2A) communication example based on Google's A2A protocol. A2A is Google's proposed standard for enabling AI agents to communicate with each other through a standardized API.

Overview

The implementation consists of two main components:

1. Server (server.py): A Flask-based server that implements the A2A protocol endpoints:

   • /.well-known/agent.json - Provides the agent's metadata (Agent Card)
   • /tasks/send - Accepts and processes tasks from other agents

2. Client (client.py): A simple client that demonstrates how to:

   • Discover an agent by fetching its Agent Card
   • Send a task to the agent
   • Process the agent's response

The example agent has web search capabilities using Brave Search through the Model Context Protocol (MCP).

Setup

1. Create a virtual environment:

   Windows:

   python -m venv venv
   venv\Scripts\activate
   

   macOS/Linux:

   python3 -m venv venv
   source venv/bin/activate
   

2. Create a .env file based on the .env.example template:

   GEMINI_API_KEY=
   BRAVE_API_KEY=your_brave_api_key
   

3. Install dependencies:

   pip install -r requirements.txt
   

4. Run the server:

   python server.py
   

5. In a separate terminal, run the client (make sure to activate the virtual environment first):

   python client.py
   

A2A Protocol

Google's A2A protocol defines a standard way for agents to communicate with each other through HTTP endpoints. The key components include:

• Agent Card: A JSON document that describes an agent's capabilities and endpoints
• Task API: Endpoints for sending tasks to agents and receiving responses
• Standardized Message Format: A consistent structure for messages exchanged between agents

For more information on Google's A2A protocol, refer to the official documentation.