MCP Server

A minimal reference implementation of the Model Context Protocol (MCP) with a few mock tools and an optional Gradio playground.

Usage

Run the server locally:

python server.py

Inside Google Colab or other notebooks use the helper:

from colab_adapter import launch_in_colab
launch_in_colab()

The API is served on port 8000 by default and the Gradio UI will try to use GRADIO_SERVER_PORT or the first free port starting at 7860.

Run in Google Colab

Open MCP_colab.ipynb in Colab or click the badge above and run the cells.

If starting from a blank notebook, run these commands to set up and launch the server:

!git clone https://github.com/zack-dev-cm/mcp_server.git
%cd /content/mcp_server
!pip install fastapi uvicorn[standard] gradio==4.* pydantic python-dotenv
from colab_adapter import launch_in_colab
launch_in_colab()

You can now query the API from another cell:

import requests, time
time.sleep(2)
print(requests.get("http://localhost:8000/v1/resources").json())

The server output shows a public URL for the Gradio interface so you can try the demo visually.

LLM/VLM Plugin Example

Plugins can extend the server with new tools. The included openai_chat and openai_vision plugins show how to call OpenAI models. Set OPENAI_API_KEY in your environment and start the server:

pip install openai
python server.py

Invoke the openai.chat or openai.vision tools via the API or Gradio UI.