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Telegram MCP 服务器

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sparfenyuk

MCP server to work with Telegram through MTProto

Publishersparfenyuk
Repositorymcp-telegram
LanguagePython
Forks
37
Stars
189
Available tools
0
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    Telegram MCP 服务器 exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    189 stars and 37 forks from the linked repository.

Telegram MCP server

About

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.

What is MCP?

The Model Context Protocol (MCP) is a system that lets AI apps, like Claude Desktop, 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?

As of not, the server provides read-only access to the Telegram API.

  • Get the list of dialogs (chats, channels, groups)
  • Get the list of (unread) messages in the given dialog
  • Mark chanel as read
  • Retrieve messages by date and time
  • Download media files
  • Get the list of contacts
  • Draft a message
  • ...

Practical use cases

  • Create a summary of the unread messages
  • Find contacts with upcoming birthdays and schedule a greeting
  • Find discussions on a given topic, summarize them and provide a list of links

Prerequisites

Installation

bash
uv tool install git+https://github.com/sparfenyuk/mcp-telegram

[!NOTE] If you have already installed the server, you can update it using uv tool upgrade --reinstall command.

[!NOTE] If you want to delete the server, use the uv tool uninstall mcp-telegram command.

Configuration

Telegram API Configuration

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:

    bash
    mcp-telegram sign-in --api-id <your-api-id> --api-hash <your-api-hash> --phone-number <your-phone-number>

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

    The password may be required if you have two-factor authentication enabled.

[!NOTE] To log out from the Telegram API, use the mcp-telegram logout command.

Claude Desktop Configuration

Configure Claude Desktop to recognize the Exa 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

    json
    {
      "mcpServers": {
        "mcp-telegram": {
            "command": "mcp-server",
            "env": {
              "TELEGRAM_API_ID": "<your-api-id>",
              "TELEGRAM_API_HASH": "<your-api-hash>",
            },
          }
        }
      }
    }

Telegram Configuration

Before working with Telegram’s API, you need to get your own API ID and hash:

  1. Login to your Telegram account with the phone number of the developer account to use.
  2. Click under API Development tools.
  3. A 'Create new application' window will appear. Fill in your application details. There is no need to enter any URL, and only the first two fields (App title and Short name) can currently be changed later.
  4. Click on 'Create application' at the end. Remember that your API hash is secret and Telegram won’t let you revoke it. Don’t post it anywhere!

Development

Getting started

  1. Clone the repository

  2. Install the dependencies

    bash
    uv sync
  3. Run the server

    bash
    uv run mcp-telegram --help

Tools can be added to the src/mcp_telegram/tools.py file.

How to add a new tool:

  1. Create a new class that inherits from ToolArgs

    python
    class NewTool(ToolArgs):
        """Description of the new tool."""
        pass

    Attributes of the class will be used as arguments for the tool. The class docstring will be used as the tool description.

  2. Implement the tool_runner function for the new class

    python
    @tool_runner.register
    async def new_tool(args: NewTool) -> t.Sequence[TextContent | ImageContent | EmbeddedResource]:
        pass

    The function should return a sequence of TextContent, ImageContent or EmbeddedResource. The function should be async and accept a single argument of the new class.

  3. Done! Restart the client and the new tool should be available.

Validation can accomplished either through Claude Desktop or by running the tool directly.

Debugging the server in terminal

To run the tool directly, use the following command:

bash

# List all available tools
uv run cli.py list-tools

# Run the concrete tool
uv run cli.py call-tool --name ListDialogs --arguments '{"unread": true}'

Debugging the server in the Inspector

The MCP inspector is a tool that helps to debug the server using fancy UI. To run it, use the following command:

bash
npx @modelcontextprotocol/inspector uv run mcp-telegram

[!WARNING] Do not forget to define Environment Variables TELEGRAM_API_ID and TELEGRAM_API_HASH in the inspector.

Troubleshooting

Message 'Could not connect to MCP server mcp-telegram'

If you see the message 'Could not connect to MCP server mcp-telegram' in Claude Desktop, it means that the server configuration is incorrect.

Try the following:

  • Use the full path to the uv binary in the configuration file
  • Check the path to the cloned repository in the configuration file

Installation

TypingMind
{
  "mcpServers": {
    "sparfenyuk-mcp-telegram": {
      "command": "uv",
      "args": [
        "run",
        "mcp-telegram"
      ],
      "env": {
        "TELEGRAM_API_ID": "<TELEGRAM_API_ID>",
        "TELEGRAM_API_HASH": "<TELEGRAM_API_HASH>"
      }
    }
  }
}

Use Telegram MCP 服务器 MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Telegram MCP 服务器 is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Telegram MCP 服务器 as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Telegram MCP 服务器 MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "sparfenyuk-mcp-telegram": {
      "command": "npx",
      "args": [
        "-y",
        "<mcp-server-package>"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Telegram MCP 服务器 MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Telegram MCP 服务器 MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Telegram MCP 服务器 to help me with this task?
Telegram MCP 服务器
Sure. I read it.
Here is what I found using Telegram MCP 服务器.

Frequently asked questions

What is the Telegram MCP 服务器 MCP server used for?

Telegram MCP 服务器 is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Telegram MCP 服务器 MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Telegram MCP 服务器 with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Telegram MCP 服务器 MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Telegram MCP 服务器 connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Telegram MCP 服务器 MCP to TypingMind?

Telegram MCP 服务器 runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Telegram MCP 服务器 MCP provide in TypingMind?

Telegram MCP 服务器 exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Telegram MCP 服务器 MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Telegram MCP 服务器 requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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