Jupyter MCP Server

<!-- ~ Copyright (c) 2023-2024 Datalayer, Inc. ~ ~ BSD 3-Clause License --> [](https://datalayer.io) [](https://github.com/sponsors/datalayer) # 🪐 ✨ Jupyter MCP Server [](https://github.com/datalayer/jupyter-mcp-server/actions/workflows/build.yml) [](https://pypi.org/project/jupyter-mcp-server) [](https://smithery.ai/server/@datalayer/jupyter-mcp-server) Jupyter MCP Server is a [Model Context Protocol](https://modelcontextprotocol.io/introduction) (MCP) server implementation that provides interaction with Jupyter notebooks 📓 running in a local JupyterLab 💻.  ## Start JupyterLab Make sure you have the following installed. The modifications made on the notebook can be seen thanks to [Jupyter Real Time Collaboration](https://jupyterlab.readthedocs.io/en/stable/user/rtc.html) (RTC). ```bash pip install jupyterlab jupyter-collaboration ipykernel ``` Then, start JupyterLab with the following command: ```bash jupyter lab --port 8888 --IdentityProvider.token MY_TOKEN --ip 0.0.0.0 ``` > [!NOTE] > The `--ip` is set to `0.0.0.0` to allow the MCP server running in a Docker container to access your local JupyterLab. ## Usage with Claude Desktop To use this with Claude Desktop, add the following to your claude_desktop_config.json: > [!IMPORTANT] > Ensure the port of the `SERVER_URL`and `TOKEN` match those used in the `jupyter lab` command. > The `NOTEBOOK_PATH` should be relative to the directory where JupyterLab was started. ### MacOS and Windows ```json { "mcpServers": { "jupyter": { "command": "docker", "args": [ "run", "-i", "--rm", "-e", "SERVER_URL", "-e", "TOKEN", "-e", "NOTEBOOK_PATH", "datalayer/jupyter-mcp-server:latest" ], "env": { "SERVER_URL": "http://host.docker.internal:8888", "TOKEN": "MY_TOKEN", "NOTEBOOK_PATH": "notebook.ipynb" } } } } ``` ### Linux ```json { "mcpServers": { "jupyter": { "command": "docker", "args": [ "run", "-i", "--rm", "-e", "SERVER_URL", "-e", "TOKEN", "-e", "NOTEBOOK_PATH", "--network=host", "datalayer/jupyter-mcp-server:latest" ], "env": { "SERVER_URL": "http://localhost:8888", "TOKEN": "MY_TOKEN", "NOTEBOOK_PATH": "notebook.ipynb" } } } } ``` ## Components ### Tools The server currently offers 3 tools: 1. `add_execute_code_cell` - Add and execute a code cell in a Jupyter notebook. - Input: - `cell_content`(string): Code to be executed. - Returns: Cell output. 2. `add_markdown_cell` - Add a markdown cell in a Jupyter notebook. - Input: - `cell_content`(string): Markdown content. - Returns: Success message. 3. `download_earth_data_granules` ⚠️ We plan to migrate this tool to a separate repository in the future as it is specific to Geospatial analysis. - Add a code cell in a Jupyter notebook to download Earth data granules from NASA Earth Data. - Input: - `folder_name`(string): Local folder name to save the data. - `short_name`(string): Short name of the Earth dataset to download. - `count`(int): Number of data granules to download. - `temporal` (tuple): (Optional) Temporal range in the format (date_from, date_to). - `bounding_box` (tuple): (Optional) Bounding box in the format (lower_left_lon, lower_left_lat, upper_right_lon, upper_right_lat). - Returns: Cell output. ## Building ```bash docker build -t datalayer/jupyter-mcp-server . ``` ## Installing via Smithery To install Jupyter MCP Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@datalayer/jupyter-mcp-server): ```bash npx -y @smithery/cli install @datalayer/jupyter-mcp-server --client claude ```