What external dependencies are required?
Lynx (for the lynx server), Docker (for puppeteer and github servers), and Node.js (for the fs server).
@WillChangeThisLater
基本情報
Use MCP servers with OpenAI Agents
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": {
"easy-mcp": {
"command": "python",
"args": [
"agent.py"
]
}
}
}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。
Project Overview combines MCP (Model Context Protocol) servers with OpenAI agents, enabling automated research and file system tasks. It is intended for developers who want to run configurable, multi-server AI agents from the command line.
Set up the environment with the provided setup.sh script (Python 3.13 virtual environment + dependencies), install required external tools (Lynx for web search, Docker for puppeteer/GitHub, Node.js for file system server), configure servers in servers.yaml, then run python agent.py with optional --servers flags (e.g., python agent.py --servers fs lynx) or --debug for testing setup.
mcp-servers directoryLynx (for the lynx server), Docker (for puppeteer and github servers), and Node.js (for the fs server).
Edit `servers.yaml` with the server's name, description, command/arguments, and environment variables. Then select servers at runtime with the `--servers` flag.
Yes, use `python agent.py --servers <server1> <server2>`. This can improve performance by reducing the chance the agent picks the wrong tool.
Use the `--debug` flag to initialize servers without executing the agent: `python agent.py --debug`.
Yes, you can add custom servers in the `mcp-servers` directory.

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