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Google A2A Agent Example MCP Server

@system32miro

リポジトリ

基本情報

カテゴリ

AI とエージェント

トランスポート

stdio

作者

system32miro

Google A2A Agent Example MCP Server について

Example implementation of the Google A2A protocol with a Flask server and Python client. Includes web search integration via MCP

#google-a2a#a2a-communication#flask-server

Google A2A Agent Example MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "google-a2a-agent": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

Google A2A Agent Example MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Google A2A Agent Example?

Google A2A Agent Example implements a simple Agent-to-Agent (A2A) communication system based on Google's proposed A2A protocol. It consists of a Flask-based server that acts as an AI agent and a Python client that demonstrates agent discovery and task exchange.

How to use Google A2A Agent Example?

Clone the repository, create a virtual environment, add your OpenAI and Brave API keys to a .env file, and install dependencies. Run python server.py in one terminal and python client.py in a separate terminal to send a predefined question and receive the agent's response.

Key features of Google A2A Agent Example

  • Implements core Google A2A protocol endpoints (/.well-known/agent.json, /tasks/send)
  • Uses OpenAI's GPT-4o-mini for AI query processing
  • Integrates Brave Search via MCP (Model Context Protocol) for web searches
  • Provides a client script demonstrating agent discovery and task submission
  • Manages external tool interactions through the pydantic-ai library

Use cases of Google A2A Agent Example

  • Prototyping agent-to-agent communication with Google's A2A standard
  • Building an AI agent that can perform web searches via Brave Search
  • Demonstrating agent discovery and task exchange for developer education

よくある質問

1

What is the Google A2A protocol?

A2A is Google's proposed standard for enabling AI agents to communicate with each other through a standardized HTTP API, using an Agent Card for discovery and a Task API for exchanging messages.

2

What API keys are required?

You need an OpenAI API key (for GPT-4o-mini) and a Brave API key (for Brave Search), stored in a `.env` file as `OPENAI_API_KEY` and `BRAVE_API_KEY`.

3

How does the architecture work?

The client discovers the agent by fetching its Agent Card, sends a task to `/tasks/send`, the server processes the query using OpenAI and optionally calls Brave Search via MCP, and returns the final response to the client.

4

Does this implementation cover the full A2A protocol?

No, this example only implements the essential `/tasks/send` endpoint and Agent Card discovery, not the full A2A protocol specification.

5

Where does data processing occur?

All AI processing and tool integration (OpenAI API calls and Brave Search requests) happen server-side. The client only sends the initial task and receives the final response.

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