Telegram MCP Server

Telegram MCP Server

The Telegram MCP Server bridges an AI assistant’s Model Context Protocol (MCP) workflow with a personal Telegram account via the official MTProto client library. Instead of relying on the limited bot API, it authenticates as a real user and exposes a rich set of tools that let assistants read, search, and archive conversations. For developers building AI‑powered chatbots or knowledge bases that need instant access to a user’s Telegram history, this server eliminates the friction of manual data export or custom API wrappers.

The core value lies in its seamless integration with MCP clients such as Claude Desktop, Cursor, or any SDK‑compatible assistant. Once the server is running, a client automatically performs the standard MCP handshake () and gains access to a suite of Telegram‑specific tools. These include listing dialogs, searching by title or username, fetching recent messages with optional regex filtering, and scheduling background sync jobs that persist dialogs into a local SQLite database. The background worker runs sequentially, ensuring consistent state and avoiding race conditions while keeping the user’s message history up‑to‑date.

Key capabilities are delivered through a clean, declarative API:

• Channel Discovery – and provide quick navigation of all accessible dialogs, making it trivial for an assistant to locate a conversation of interest.
• Message Retrieval – returns recent messages by ID or username, optionally filtered with regular expressions, enabling fine‑grained data extraction without manual scrolling.
• Background Archival – queues a job that writes the entire dialog into an SQLite archive, while exposes job status and cursors for monitoring.
• Persistent Sessions – The server stores an MTProto session file (), so users are prompted only once for login and 2FA, streamlining repeated use.

In real‑world scenarios this server shines when building context‑aware assistants that need to pull in recent Telegram discussions, integrate chat logs into a knowledge graph, or provide on‑demand archival for compliance. For example, an enterprise AI tool can automatically sync team channels to a local database and let the assistant answer queries about past decisions. Similarly, personal assistants can fetch family group chats or support threads on demand, all while preserving privacy by keeping data local.

Because the server operates over standard HTTP with a streamable transport, it fits naturally into existing MCP workflows. Developers can spin up the service locally or host it in a secure environment, then point their MCP client to . The sequential background worker and SQLite storage guarantee consistent, reproducible results without external dependencies. This combination of user‑level access, lightweight persistence, and MCP compatibility gives the Telegram MCP Server a distinctive edge for developers looking to fuse AI assistants with their personal messaging ecosystems.