mcp-client-jupyter-chat
Advanced tools
A JupyterLab extension for Chat with AI supporting Model Context Protocol (MCP). This extension integrates AI and provides interactive tool usage capabilities through MCP servers.
The extension supports multiple Claude models through the Anthropic API. You'll need to:
To install the extension, execute:
pip install mcp_client_jupyter_chat
To remove the extension, execute:
pip uninstall mcp_client_jupyter_chat
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 mcp_client_jupyter_chat directory
# Install package in development mode
pip install -e "."
# Link your development version of the extension with JupyterLab
jupyter labextension develop . --overwrite
# 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
pip uninstall mcp_client_jupyter_chat
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 mcp-client-jupyter-chat within that folder.
This extension is using Jest for JavaScript code testing.
To execute them, execute:
jlpm
jlpm test
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.
See RELEASE
FAQs
A JupyterLab extension for Chat with AI supporting MCP
We found that mcp-client-jupyter-chat demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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