Telegram logo

Telegram

Community
chaindead

Telegram MCP for managing dialogs, messages, drafts, read statuses, and more.

Publisherchaindead
Repositorytelegram-mcp
LanguageGo
Forks
45
Stars
326
Available tools
0
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    Telegram 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

    326 stars and 45 forks from the linked repository.

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?

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:

bash
# 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):

bash
npx -y @chaindead/telegram-mcp

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

bash
npx -y @chaindead/telegram-mcp auth ...
json
{
  "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:

bash
# 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:

bash
# 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:

bash
# 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:

bash
# 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:
  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
bash
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

    bash
    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:

    json
     {
       "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:

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

JSON Schema Version

Some MCP clients (e.g. VS Code) do not support JSON Schema Draft 2020-12 and will reject tools that use it. You can override the JSON Schema version by setting the --schema-version flag or the TG_SCHEMA_VERSION environment variable.

Common values:

VersionURL
Draft-07 (recommended for VS Code)https://json-schema.org/draft-07/schema#
Draft 2020-12 (default)https://json-schema.org/draft/2020-12/schema

Star History

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "telegram": {
      "command": "npx",
      "args": [
        "-y",
        "@chaindead/telegram-mcp"
      ],
      "env": {
        "TG_APP_ID": "<your-api-id>",
        "TG_API_HASH": "<your-api-hash>"
      }
    }
  }
}

Use Telegram MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Telegram 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 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 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": {
    "telegram": {
      "command": "npx",
      "args": [
        "-y",
        "@chaindead/telegram-mcp"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Telegram 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 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 to help me with this task?
Telegram
Sure. I read it.
Here is what I found using Telegram.

Frequently asked questions

What is the Telegram MCP server used for?

Telegram 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 with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Telegram 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 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 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 to TypingMind?

Telegram 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 provide in TypingMind?

Telegram 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?

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

Related MCP Servers

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇