Quirox Telegram Bot Backend

Name: Quirox Telegram Bot Backend
Author: Himank-J

@Himank-J

关于 Quirox Telegram Bot Backend

This repo demonstrates how to build a telegram bot using SSE Server and implement agentic flow using MCP with tools like Gmail, GDrive

#telegram-bot #ai-agent #tool-integration

基本信息

分类

沟通协作

运行时

python

传输方式

stdio

发布者

Himank-J

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "Quirox-Telegram-Bot": {
      "command": "python",
      "args": [
        "mcp_server.py"
      ]
    }
  }
}

工具

未检测到工具

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 Quirox Telegram Bot Backend?

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.

How to use Quirox Telegram Bot Backend?

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.

Key features of Quirox Telegram Bot Backend

AI agent using Google Gemini Flash model for reasoning and task execution.
Google Sheets integration: create, read, write, manage sheets, share.
Web search via DuckDuckGo and web content fetching from URLs.
FastAPI web server exposing a /chat endpoint for HTTP interactions.
MCP framework managing communication between AI model and tools.

Use cases of Quirox Telegram Bot Backend

Automate spreadsheet creation, data entry, and sheet management via chat.
Perform web searches and retrieve content from URLs through conversational commands.
Extend a Telegram bot with AI-powered tool interactions for document or data workflows.

FAQ from Quirox Telegram Bot Backend

What are the prerequisites?

Python 3.8+, access to Google Cloud Platform for Sheets/Drive API, and a Google Gemini API key.

How do I authenticate with Google services?

You can use a service account (recommended for servers) or OAuth 2.0. Provide the credentials via environment variables in the .env file.

How do I interact with the backend?

Send POST requests to http://localhost:8000/chat (or your server’s address) with a JSON body containing a "message" field.

Are Gmail tools available?

Gmail functions are present in the code but currently commented out and not exposed in the running server.

What dependencies does the project require?

Key dependencies include fastapi, uvicorn, mcp, google-api-python-client, google-generativeai, httpx, beautifulsoup4, and others listed in requirements.txt.

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