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Jupyter MCP Server

by datalayer
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local-only server

The server can only run on the client’s local machine because it depends on local resources.

Integrations

  • Provides interaction with Jupyter notebooks running in JupyterLab, allowing adding and executing code cells, creating markdown cells, and interacting with notebook content programmatically.

  • Offers functionality to download Earth data granules from NASA Earth Data, supporting parameters for folder name, dataset short name, count, temporal range, and bounding box.

🪐 ✨ Jupyter MCP Server

Jupyter MCP Server is a Model Context Protocol (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 (RTC).

pip install jupyterlab jupyter-collaboration ipykernel

Then, start JupyterLab with the following command:

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_URLand 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

{ "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

{ "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.
  1. add_markdown_cell
  • Add a markdown cell in a Jupyter notebook.
  • Input:
    • cell_content(string): Markdown content.
  • Returns: Success message.
  1. 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

docker build -t datalayer/jupyter-mcp-server .

Installing via Smithery

To install Jupyter MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @datalayer/jupyter-mcp-server --client claude

This server cannot be installed

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Enables interaction with Jupyter notebooks through the Model Context Protocol, supporting code execution and markdown insertion within JupyterLab environments.

  1. Start JupyterLab
    1. Usage with Claude Desktop
      1. MacOS and Windows
      2. Linux
    2. Components
      1. Tools
    3. Building
      1. Installing via Smithery

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