广告合作
MCP.so
登录

Google A2A Agent Example MCP Server

@system32miro

代码仓库

基本信息

分类

AI 与智能体

传输方式

stdio

作者

system32miro

关于 Google A2A Agent Example MCP Server

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 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

Google A2A Agent Example MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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

常见问题

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.

评论

AI 与智能体 分类下的更多 MCP 服务器

Krafters

Krafters (Romain Duclos)

Krafters is a French club of specialized AIs for freelancers and small businesses. Its connector opens the member's AI kits for Facebook and Instagram ads, SEO/GEO and short videos directly in Claude, and gives the next

AON — Agent Offer Network

AON

AON MCP connects AI agents to real, buyable products and services with live pricing and tracked links—enabling builders to earn developer revenue share from attributed clicks and conversions.

2

AgentRisk M2M

Neurobyteio

AgentRisk M2M 🛡️ The Security & Trust Layer for Autonomous Agents on Base. Stop letting your trading agents get rekt by stealth honeypots, dynamic sell-blocks, and rugpulls that pass every static check. ⚡ The Problem

Atwork

Atwork Team

Connect Atwork to Claude, ChatGPT, Cursor or any MCP client and work with your real data: ask what is overdue, total a sheet by any field, add tasks, update rows, post comments and draft pages. The assistant acts as you

Rumoro

@Rumoro

Social listening for AI agents. Rumoro's remote MCP server lets Claude, Cursor, Codex and other MCP clients search and sort mentions of your product, your competitors and your topics on Reddit, X, Hacker News, GitHub, Yo

广告合作