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telegram-ai-mcp-assistant-bot

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Telegram AI Assistant Bot that responds to user messages using multiple MCP Servers

6 stars PythonCommunication Updated Oct 17, 2025

Documentation

Telegram AI Assistant Bot

Overview

The Telegram AI Assistant Bot is a reasoning-driven AI agent, named Cortex-R, designed to interact with users via Telegram. It uses multiple Model Context Protocol (MCP) servers to perform various tasks such as web searches, document processing, mathematical calculations, and Google services integration (e.g., Gmail and Google Sheets). The bot employs both `stdio` and `sse` transport protocols to communicate with these MCP servers.

Features

  • Telegram Integration: The bot interacts with users through Telegram, responding to their queries and tasks.
  • Multi-MCP Server Support: Utilizes multiple MCP servers for diverse functionalities.
    • Gmail integration for email management.
    • Google Sheets integration for spreadsheet operations.
    • Web search capabilities using DuckDuckGo.
    • Document processing and semantic search.
    • Mathematical calculations.
  • Dynamic Tool Discovery: Automatically discovers tools from MCP servers during initialization.
  • Customizable Agent Strategy: Supports different strategies like conservative, retry-once, and explore-all.
  • Memory Management: Retrieves and stores memory items to enhance task-solving capabilities.
  • Configurable Persona: Allows customization of tone, verbosity, and behavior.

Architecture

The bot is built using the following components:

1. Telegram Bot Integration

The bot is implemented in `telegram_agent.py` using the `python-telegram-bot` library. It handles user messages and commands such as `/start` and `/help`. User queries are processed by the Cortex-R agent.

2. Core Components

  • Agent Loop (`core/loop.py`): Manages the main execution loop of the agent, including perception, planning, and tool execution.
  • Session Management (`core/session.py`): Handles communication with multiple MCP servers using `stdio` and `sse` transport protocols.
  • Strategy (`core/strategy.py`): Implements planning strategies for decision-making.

3. MCP Servers

The bot interacts with the following MCP servers:

  • Gmail Server (`gmail_server.py`): Manages email operations such as sending, reading, and trashing emails.
  • Google Sheets Server (`mcp_gdrive_server.py`): Handles spreadsheet operations like creating, updating, and sharing Google Sheets.
  • Web Search Server (`mcp_server_3.py`): Performs web searches using DuckDuckGo and fetches webpage content.
  • Document Processing Server (`mcp_server_2.py`): Processes documents for semantic search and indexing.
  • Math Server (`mcp_server_1.py`): Performs mathematical calculations.

4. Configuration

  • Profiles (`config/profiles.yaml`): Defines agent settings, including strategy, memory configuration, and MCP server details.
  • Models (`config/models.json`): Specifies the models used for text generation and embeddings.
  • Environment Variables (`.env`): Stores sensitive information like API keys and file paths.

Workflow

1. Initialization:

    2. User Interaction:

      3. Task Execution:

        4. Memory Management:

          Configuration

          Environment Variables

          Set the following variables in the `.env` file:

          • `GEMINI_API_KEY`: API key for the Gemini model.
          • `SERVICE_ACCOUNT_PATH`: Path to the Google service account JSON file.
          • `DRIVE_FOLDER_ID`: Google Drive folder ID for storing files.
          • `CREDENTIALS_PATH`: Path to the OAuth client credentials file.
          • `TOKEN_PATH`: Path to the token file for Google APIs.

          MCP Server Configuration

          Define MCP servers in `config/profiles.yaml`:

          yaml
          mcp_servers:
            - id: gmail
              type: stdio
              script: gmail_server.py
              cwd: 
            - id: gdrive
              type: stdio
              script: mcp_gdrive_server.py
              cwd: 
            - id: math
              type: sse
              script: mcp_server_1.py
              url: http://localhost:8000/sse
              cwd: 
            - id: documents
              type: stdio
              script: mcp_server_2.py
              cwd: 
            - id: websearch
              type: stdio
              script: mcp_server_3.py
              cwd:

          Installation

          1. Clone the repository:

          bash
          git clone 
             cd

          2. Sync dependencies using uv:

          bash
          uv sync

          3. Set up environment variables in `.env`.

          4. Start the Telegram bot:

          bash
          uv run telegram_agent.py

          Usage

          • Start the bot on Telegram using the `/start` command.
          • Send queries or tasks to the bot, such as:
            • "Find the current F1 standings and share them in a Google Sheet."
            • "Send an email to example@gmail.com with the subject 'Meeting Update'."

          Contributing

          Contributions are welcome! Please follow these steps:

          1. Fork the repository.

          2. Create a new branch for your feature or bug fix.

          3. Submit a pull request with a detailed description of your changes.

          License

          This project is licensed under the MIT License. See the `LICENSE` file for details.

          Frequently asked questions

          What is telegram-ai-mcp-assistant-bot?

          telegram-ai-mcp-assistant-bot is Telegram AI Assistant Bot that responds to user messages using multiple MCP Servers

          How do I install telegram-ai-mcp-assistant-bot?

          Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.

          Is telegram-ai-mcp-assistant-bot open source?

          Yes — it is hosted on GitHub at https://github.com/shettysaish20/Telegram-AI-MCP-Assistant-Bot and has 6 stars.

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