Telegram MCP Server Integration

What does “Telegram” MCP Server do?

The Telegram MCP Server acts as a bridge between the Telegram API and AI assistants using the Model Context Protocol (MCP). It enables AI-driven workflows to interact directly with Telegram, allowing for management of dialogs, messages, drafts, read statuses, and more. This server empowers developers to automate Telegram tasks, integrate messaging data into broader AI pipelines, and streamline communication workflows. With this integration, AI clients can read, organize, and send messages, manage contacts, and automate common Telegram interactions, significantly enhancing productivity and enabling advanced automation scenarios for individuals and teams.

List of Prompts

• Message Management: Templates to retrieve, organize, and summarize chats or messages from Telegram.
• Organization: Prompts to structure, categorize, or prioritize messages and conversations.
• Communication: Standardized prompts for sending, replying, or forwarding messages to contacts or groups.

List of Resources

• Dialogs: Access to a user’s active chats and dialog history.
• Messages: Read and analyze message content from selected chats.
• Drafts: Manage unsent or draft messages within Telegram.
• Read Statuses: Track which messages have been read or are unread.

List of Tools

• Dialog Management Tool: Manage and retrieve dialog lists.
• Message Sender/Receiver Tool: Send, receive, or reply to messages.
• Draft Management Tool: Access, create, or delete message drafts.
• Read Status Tool: Mark messages as read or unread.

Use Cases of this MCP Server

• Automated Chat Summarization: Use the server to fetch and summarize large volumes of chat messages, helping users quickly catch up on missed conversations.
• Personal Messaging Assistant: Automate sending routine updates, replies, or notifications to Telegram contacts using AI-driven prompts.
• Contact and Group Organization: Categorize and prioritize chats or groups, making it easier to manage communication at scale.
• Draft Automation: Automatically generate and manage message drafts based on calendar events or reminders.
• Monitoring and Alerting: Integrate Telegram with monitoring tools to receive instant alerts or status updates directly in Telegram chats.

How to set it up

Windsurf

1. Ensure you have Node.js installed.
2. Open your Windsurf configuration file.
3. Add the Telegram MCP Server using the following JSON snippet:

   {
     "mcpServers": {
       "telegram-mcp": {
         "command": "npx",
         "args": ["@telegram/mcp-server@latest"]
       }
     }
   }
   

4. Save the configuration and restart Windsurf.
5. Verify the server is running by checking the MCP connection status.

Claude

1. Install Node.js if not already present.
2. Locate the Claude configuration file.
3. Add the Telegram MCP Server configuration:

   {
     "mcpServers": {
       "telegram-mcp": {
         "command": "npx",
         "args": ["@telegram/mcp-server@latest"]
       }
     }
   }
   

4. Save changes and restart Claude.
5. Confirm integration by initiating a Telegram MCP workflow.

Cursor

1. Ensure prerequisites like Node.js are installed.
2. Edit the Cursor configuration file.
3. Insert the following MCP server entry:

   {
     "mcpServers": {
       "telegram-mcp": {
         "command": "npx",
         "args": ["@telegram/mcp-server@latest"]
       }
     }
   }
   

4. Restart Cursor to apply changes.
5. Test the setup by connecting to Telegram MCP.

Cline

1. Make sure Node.js is set up on your system.
2. Access the Cline config file.
3. Add the Telegram MCP Server:

   {
     "mcpServers": {
       "telegram-mcp": {
         "command": "npx",
         "args": ["@telegram/mcp-server@latest"]
       }
     }
   }
   

4. Save and restart Cline.
5. Check that the server is active and accessible.

Securing API keys

To secure API keys, use environment variables in your configuration:

{
  "mcpServers": {
    "telegram-mcp": {
      "command": "npx",
      "args": ["@telegram/mcp-server@latest"],
      "env": {
        "TELEGRAM_API_KEY": "${TELEGRAM_API_KEY}"
      },
      "inputs": {
        "apiKey": "${TELEGRAM_API_KEY}"
      }
    }
  }
}

This ensures sensitive keys are not stored in plain text within configuration files.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "telegram-mcp": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “telegram-mcp” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the information found, the Telegram MCP Server offers a robust integration with Telegram for AI assistants, clearly listing MCP primitives (resources, tools, prompts) and providing practical setup and security guidance. Sampling and Roots support are not documented. The repo is open source and has community engagement.

Our opinion

This MCP server is well-documented and offers a clear, practical bridge between Telegram and AI workflows. It’s open-source with an MIT license, provides real-world automation tools, and includes detailed setup instructions. Lack of explicit Sampling/Roots support documentation is a minor drawback. Overall, it’s a strong, useful MCP server for communication automation.

MCP Score