MCP Cursor

Enhance your development workflow with AI-powered MCP tools and extensions for Cursor IDE.

Product

  • MCP Servers
  • Getting Started
  • Documentation
  • Open Source

Resources

  • MCP Specification
  • Cursor IDE
  • MCP GitHub
  • Contributing

Legal

  • Privacy Policy
  • Terms of Service
  • Cookie Policy
Made withfor the developer community
© 2025 MCP Cursor. All rights reserved.
MCP Logo
MCP Cursor
IntroductionMCPs
IntroductionMCPs
3D MCP Cursor Visualization
  1. Home
  2. Servers
  3. Telegram MCP server MCP
Telegram MCP server MCP Logo

Telegram MCP server MCP

Model Context Protocol Integration

Overview

Telegram API integration for accessing user data, managing dialogs (chats, channels, groups), retrieving messages, and handling read status

# Telegram MCP

Telegram API integration for accessing user data, managing dialogs (chats, channels, groups), retrieving messages, and handling read status

Installation Instructions


README: https://github.com/chaindead/telegram-mcp

License: MIT Visitors

Telegram MCP server

The server is a bridge between the Telegram API and the AI assistants and is based on the Model Context Protocol.

[!IMPORTANT] Ensure that you have read and understood the Telegram API Terms of Service before using this server. Any misuse of the Telegram API may result in the suspension of your account.

Table of Contents

  • What is MCP?
  • What does this server do?
    • Capabilities
    • Prompt examples
      • Message Management
      • Organization
      • Communication
  • Installation
    • Homebrew
    • NPX
    • From Releases
      • MacOS
      • Linux
      • Windows
    • From Source
  • Configuration
    • Authorization
    • Client Configuration
  • Star History

What is MCP?

The Model Context Protocol (MCP) is a system that lets AI apps, like Claude Desktop or Cursor, connect to external tools and data sources. It gives a clear and safe way for AI assistants to work with local services and APIs while keeping the user in control.

What does this server do?

Capabilities

  • Get current account information (tool: tg_me)
  • List dialogs with optional unread filter (tool: tg_dialogs)
  • Mark dialog as read (tool: tg_read)
  • Retrieve messages from specific dialog (tool: tg_dialog)
  • Send draft messages to any dialog (tool: tg_send)

Prompt examples

Here are some example prompts you can use with AI assistants:

Message Management

  • "Check for any unread important messages in my Telegram"
  • "Summarize all my unread Telegram messages"
  • "Read and analyze my unread messages, prepare draft responses where needed"
  • "Check non-critical unread messages and give me a brief overview"

Organization

  • "Analyze my Telegram dialogs and suggest a folder structure"
  • "Help me categorize my Telegram chats by importance"
  • "Find all work-related conversations and suggest how to organize them"

Communication

  • "Monitor specific chat for updates about [topic]"
  • "Draft a polite response to the last message in [chat]"
  • "Check if there are any unanswered questions in my chats"

Installation

Homebrew

You can install a binary release on macOS/Linux using brew:

# Install
brew install chaindead/tap/telegram-mcp

# Update
brew upgrade chaindead/tap/telegram-mcp

NPX

You can run the latest version directly using npx (supports macOS, Linux, and Windows):

npx -y @chaindead/telegram-mcp

When using NPX, modify the standard commands and configuration as follows:

  • Authentication command becomes:
npx -y @chaindead/telegram-mcp auth ...
  • Claude MCP server configuration becomes:
{
  "mcpServers": {
    "telegram": {
      "command": "npx",
      "args": ["-y", "@chaindead/telegram-mcp"],
      "env": {
        "TG_APP_ID": "<your-api-id>",
        "TG_API_HASH": "<your-api-hash>"
      }
    }
  }
}

For complete setup instructions, see Authorization and Client Configuration.

From Releases

MacOS

Note: The commands below install to /usr/local/bin. To install elsewhere, replace /usr/local/bin with your preferred directory in your PATH.

First, download the archive for your architecture:

# For Intel Mac (x86_64)
curl -L -o telegram-mcp.tar.gz https://github.com/chaindead/telegram-mcp/releases/latest/download/telegram-mcp_Darwin_x86_64.tar.gz

# For Apple Silicon (M1/M2)
curl -L -o telegram-mcp.tar.gz https://github.com/chaindead/telegram-mcp/releases/latest/download/telegram-mcp_Darwin_arm64.tar.gz

Then install the binary:

# Extract the binary
sudo tar xzf telegram-mcp.tar.gz -C /usr/local/bin

# Make it executable
sudo chmod +x /usr/local/bin/telegram-mcp

# Clean up
rm telegram-mcp.tar.gz

Linux

Note: The commands below install to /usr/local/bin. To install elsewhere, replace /usr/local/bin with your preferred directory in your PATH.

First, download the archive for your architecture:

# For x86_64 (64-bit)
curl -L -o telegram-mcp.tar.gz https://github.com/chaindead/telegram-mcp/releases/latest/download/telegram-mcp_Linux_x86_64.tar.gz

# For ARM64
curl -L -o telegram-mcp.tar.gz https://github.com/chaindead/telegram-mcp/releases/latest/download/telegram-mcp_Linux_arm64.tar.gz

Then install the binary:

# Extract the binary
sudo tar xzf telegram-mcp.tar.gz -C /usr/local/bin

# Make it executable
sudo chmod +x /usr/local/bin/telegram-mcp

# Clean up
rm telegram-mcp.tar.gz

Windows

Windows

  1. Download the latest release for your architecture:
    • Windows x64
    • Windows ARM64
  2. Extract the .zip file
  3. Add the extracted directory to your PATH or move telegram-mcp.exe to a directory in your PATH

From Source

Requirements:

  • Go 1.24 or later
  • GOBIN in PATH
go install github.com/chaindead/telegram-mcp@latest

Configuration

Authorization

Before you can use the server, you need to connect to the Telegram API.

  1. Get the API ID and hash from Telegram API

  2. Run the following command:

    Note: If you have 2FA enabled: add --password <2fa_password>

    Note: If you want to override existing session: add --new

    telegram-mcp auth --app-id <your-api-id> --api-hash <your-api-hash> --phone <your-phone-number>
    

    📩 Enter the code you received from Telegram to connect to the API.

  3. Done! Please give this project a ⭐️ to support its development.

Client Configuration

Example of Configuring Claude Desktop to recognize the Telegram MCP server.

  1. Open the Claude Desktop configuration file:

    • in MacOS, the configuration file is located at ~/Library/Application Support/Claude/claude_desktop_config.json
    • in Windows, the configuration file is located at %APPDATA%\Claude\claude_desktop_config.json

    Note: You can also find claude_desktop_config.json inside the settings of Claude Desktop app

  2. Add the server configuration

    for Claude desktop:

     {
       "mcpServers": {
         "telegram": {
           "command": "telegram-mcp",
           "env": {
             "TG_APP_ID": "<your-app-id>",
             "TG_API_HASH": "<your-api-hash>",
             "PATH": "<path_to_telegram-mcp_binary_dir>",
             "HOME": "<path_to_your_home_directory"
           }
         }
       }
     }
    

    for Cursor:

    {
      "mcpServers": {
        "telegram-mcp": {
          "command": "telegram-mcp",
          "env": {
            "TG_APP_ID": "<your-app-id>",
            "TG_API_HASH": "<your-api-hash>"
          }
        }
      }
    }
    

Star History

Star History Chart

Featured MCPs

Github MCP - Model Context Protocol for Cursor IDE

Github

This server provides integration with Github's issue tracking system through MCP, allowing LLMs to interact with Github issues.

Sequential Thinking MCP - Model Context Protocol for Cursor IDE

Sequential Thinking

An MCP server implementation that provides a tool for dynamic and reflective problem-solving through a structured thinking process. Break down complex problems into manageable steps, revise and refine thoughts as understanding deepens, and branch into alternative paths of reasoning.

Puppeteer MCP - Model Context Protocol for Cursor IDE

Puppeteer

A Model Context Protocol server that provides browser automation capabilities using Puppeteer. This server enables LLMs to interact with web pages, take screenshots, execute JavaScript, and perform various browser-based operations in a real browser environment.