Content
# A2A Agent to MCP server 🤖
A command-line tool that generates Model Context Protocol (MCP) server code from a oneline a2a agent. This tool helps you quickly create an MCP server that acts as a bridge between LLMs (Large Language Models) and the a2a agent.
English | [简体中文](./README-zh.md)
## Features ✨
- Automatic Tool Generation: Converts each `skills` of the a2a agent into an MCP tool
- Transport Options: Only supports stdio, for sse you can leveral mcp-proxy
- Complete Project Setup: Generates all necessary files to run an MCP server
- Easy Configuration: Simple environment-based configuration for the generated server
## Prerequisites
- Python 3.13+
- `uv` (optional, but recommended) or `pip`
## Environment Setup 🔧
Firstly, you need to start up a a2a agent:
https://github.com/google/a2a-python/tree/main/examples
```
uv run a2a-agent-mcpserver-generator --agent http://0.0.0.0:10000
```
## Installation 📦
```bash
uv pip install a2a-agent-mcpserver-generator
```
## Usage 🚀
```
uv run a2a-agent-mcpserver-generator --help
Usage: a2a-agent-mcpserver-generator [OPTIONS]
Options:
--agent TEXT
--output TEXT
--name TEXT
--history BOOLEAN
--use_push_notifications BOOLEAN
--push_notification_receiver TEXT
--help Show this message and exit.
```
## E2E example
Suggest use [mcpclihost](https://github.com/vincent-pli/mcp-cli-host) as MCP host to take a try.
This tool(`mcpclihost`) could support both Azure Openai and deepseek
You can add generated MCP server congiguration like this:
```
{
"mcpServers": {
"a2a-mcp": {
"command": "uv",
"args": [
"--project",
"/Users/lipeng/workspaces/github.com/vincent-pli/a2a-agent-mcpserver-generator/a2a-mcp-server",
"run",
"a2a-agent-mcpserver"
]
}
}
}
```
to the `~/.mcp.json`(default mcp server configuration path of `mcpclihost`), then take a try
## License 📄
This project is licensed under the Apache 2.0 License - see the [LICENSE](LICENSE) file for details.
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