How does MCP differ from function calls or agent tools?
MCP separates the LLM’s decision‑making from execution; you can swap out tools without modifying the LLM. Direct function calls or agent methods mix logic, making maintenance harder.
@arananet
Basic information
A Python-based Model Context Protocol (MCP) client and server that enables LLMs to send notifications via Telegram and receive user responses.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-telegram-poc": {
"command": "python3",
"args": [
"-m",
"venv",
".venv"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
A Python-based Model Context Protocol (MCP) client and server that enables LLMs to send notifications via Telegram and receive user responses. It decouples the LLM’s reasoning from the execution of external actions, making tool integration more modular and maintainable.
Clone the repository, install dependencies (pip install -r requirements.txt), create a virtual environment, and fill in your Telegram credentials in a .env file (Telegram bot token, chat ID, OpenAI API key). Run the server with python3 src/mcp_handler.py, or test client interaction with python3 examples/test_client.py. The server exposes two tools: send_alert (sends a Telegram message) and check_reply (polls for replies).
MCP separates the LLM’s decision‑making from execution; you can swap out tools without modifying the LLM. Direct function calls or agent methods mix logic, making maintenance harder.
Python 3.11+, a Telegram bot token (from @BotFather), your Telegram chat ID, and an OpenAI API key.
Chat with @BotFather on Telegram, send `/newbot`, and follow the prompts. To find your chat ID, send a message to your bot, then visit `https://api.telegram.org/bot<YOUR_BOT_TOKEN>/getUpdates` and look for the `chat` object’s `id` field.
The server runs as a standalone Python script. Use a virtual environment and install dependencies from `requirements.txt`. It is tested on Linux/macOS.
The README does not specify limits beyond the configurable `timeout_seconds` for `check_reply` (default 60 seconds). The server uses polling for replies.

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