What are the prerequisites?
You need a Telegram API ID, API hash, and a phone number. These are set in a `.env` file alongside an optional `PORT` variable (defaults to 3000).
@MCP-Mirror
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This project provides both a Telegram client library and an MCP (Model Context Protocol) server for AI assistants to interact with Telegram. It’s for developers who want to build AI-powered tools that can read, search, and manage Telegram channels and messages.
Set up a .env file with your Telegram API credentials, then run npm install to install dependencies. Start the MCP server with npm start (defaults to port 3000) and connect any MCP‑compatible assistant (e.g., Claude) to the server endpoint. You can also use the standalone client library directly in Node.js scripts.
You need a Telegram API ID, API hash, and a phone number. These are set in a `.env` file alongside an optional `PORT` variable (defaults to 3000).
The library handles login (including 2FA) and automatically reuses saved sessions so you don’t need to re‑authenticate each time.
Session files are saved to `./data/session.json` by default. You can override this path in the `TelegramClient` constructor.
Yes. The MCP server exposes tools that any MCP‑compatible assistant can call to search channels, list channels, get messages, and filter by pattern.
The server uses an HTTP/SSE transport layer, listening for connections on the configured port.
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