🪐✨ Jupyter MCP Tools

This extension is composed of a Python package named jupyter_mcp_tools for the server extension and a NPM package named @datalayer/jupyter-mcp-tools for the frontend extension.

It enables the use of JupyterLab commands as MCP tools.

This extension is used by jupyter-mcp-server to enable JupyterLab commands such as opening notebooks through MCP tools.

Execution Modes

The extension supports two execution modes for JupyterLab commands:

Local Mode

• Direct Execution: Commands are executed directly within the JupyterLab frontend using the built-in command registry
• No Network Required: Immediate execution without WebSocket communication
• Use Case: Testing commands and direct UI interaction within JupyterLab itself
• Implementation: Calls app.commands.execute() directly in the browser

Remote Mode

• WebSocket Communication: Commands are sent via WebSocket to the backend server extension
• External Access: Enables external MCP clients to execute JupyterLab commands remotely
• Use Case: Integration with AI agents and MCP clients like jupyter-mcp-server
• Implementation: Messages are transmitted through WebSocket protocol to backend handlers

The remote mode is what makes this extension valuable for MCP integration - it allows AI agents to trigger JupyterLab commands (like opening notebooks, executing cells, etc.) from outside the JupyterLab environment through a standardized protocol.

Requirements

• JupyterLab >= 4.0.0

Install

To install the extension, execute:

pip install jupyter_mcp_tools

Use

make start

Uninstall

To remove the extension, execute:

pip uninstall jupyter_mcp_tools

Troubleshoot

If you are seeing the frontend extension, but it is not working, check that the server extension is enabled:

jupyter server extension list

If the server extension is installed and enabled, but you are not seeing the frontend extension, check the frontend extension is installed:

jupyter labextension list

Contributing

Development install

Note: You will need NodeJS to build the extension package.

The jlpm command is JupyterLab's pinned version of yarn that is installed with JupyterLab. You may use yarn or npm in lieu of jlpm below.

# Clone the repo to your local environment
# Change directory to the jupyter_mcp_tools directory
# Install package in development mode
pip install -e ".[test]"
# Link your development version of the extension with JupyterLab
jupyter labextension develop . --overwrite
# Server extension must be manually installed in develop mode
jupyter server extension enable jupyter_mcp_tools
# Rebuild extension Typescript source after making changes
jlpm build

You can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.

# Watch the source directory in one terminal, automatically rebuilding when needed
jlpm watch
# Run JupyterLab in another terminal
jupyter lab

With the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).

By default, the jlpm build command generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:

jupyter lab build --minimize=False

Development uninstall

# Server extension must be manually disabled in develop mode
jupyter server extension disable jupyter_mcp_tools
pip uninstall jupyter_mcp_tools

In development mode, you will also need to remove the symlink created by jupyter labextension develop command. To find its location, you can run jupyter labextension list to figure out where the labextensions folder is located. Then you can remove the symlink named @datalayer/jupyter-mcp-tools within that folder.

Testing the extension

Server tests

This extension is using Pytest for Python code testing.

Install test dependencies (needed only once):

pip install -e ".[test]"
# Each time you install the Python package, you need to restore the front-end extension link
jupyter labextension develop . --overwrite

To execute them, run:

pytest -vv -r ap --cov jupyter_mcp_tools

Frontend tests

This extension is using Jest for JavaScript code testing.

To execute them, execute:

jlpm
jlpm test

Integration tests

This extension uses Playwright for the integration tests (aka user level tests). More precisely, the JupyterLab helper Galata is used to handle testing the extension in JupyterLab.

More information are provided within the ui-tests README.

Packaging the extension

See RELEASE