What are the prerequisites?
Python 3.8+, access to Google Cloud Platform for Sheets/Drive API, and a Google Gemini API key.
@Himank-J
基本情報
This repo demonstrates how to build a telegram bot using SSE Server and implement agentic flow using MCP with tools like Gmail, GDrive
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": {
"Quirox-Telegram-Bot": {
"command": "python",
"args": [
"mcp_server.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。
Quirox Telegram Bot Backend provides backend services for a Telegram bot, featuring an AI agent powered by Google Gemini that can interact with tools like Google Sheets, web search (DuckDuckGo), and web content fetching. It uses the Model Context Protocol (MCP) to manage communication between the AI model and the tools, and exposes a FastAPI web server.
Set up a .env file with your Google Gemini API key and Google Cloud credentials (service account or OAuth). Run python mcp_server.py in one terminal, then python main.py in another. Send POST requests to the /chat endpoint with a JSON body containing a "message" field to interact with the AI agent.
/chat endpoint for HTTP interactions.Python 3.8+, access to Google Cloud Platform for Sheets/Drive API, and a Google Gemini API key.
You can use a service account (recommended for servers) or OAuth 2.0. Provide the credentials via environment variables in the `.env` file.
Send POST requests to `http://localhost:8000/chat` (or your server’s address) with a JSON body containing a `"message"` field.
Gmail functions are present in the code but currently commented out and not exposed in the running server.
Key dependencies include `fastapi`, `uvicorn`, `mcp`, `google-api-python-client`, `google-generativeai`, `httpx`, `beautifulsoup4`, and others listed in `requirements.txt`.

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