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jupyter_ai_tools
jupyter_ai_tools
is a Jupyter Server extension that exposes a collection of powerful, agent-friendly tools for interacting with notebooks and Git repositories. It is designed for use by AI personas (like those in Jupyter AI) to programmatically modify notebooks, manage code cells, and interact with version control systems.
✨ Features
This extension provides runtime-discoverable tools compatible with OpenAI-style function calling or MCP tool schemas. These tools can be invoked by agents to:
🧠 YNotebook Tools
read_cell
: Return the full content of a cell by indexread_notebook
: Return all cells as a JSON-formatted listadd_cell
: Insert a blank cell at a specific indexdelete_cell
: Remove a cell and return its contentswrite_to_cell
: Overwrite the content of a cell with new sourceget_max_cell_index
: Return the last valid cell index
🌀 Git Tools
git_clone
: Clone a Git repo into a given pathgit_status
: Get the working tree statusgit_log
: View recent commit historygit_add
: Stage files (individually or all)git_commit
: Commit staged changes with a messagegit_push
: Push local changes to a remote branchgit_pull
: Pull remote updatesgit_get_repo_root_from_notebookpath
: Find the Git root from a notebook path
These tools are ideal for agents that assist users with code editing, version control, or dynamic notebook interaction.
Requirements
- Jupyter Server
Install
To install the extension, execute:
pip install jupyter_ai_tools
Uninstall
To remove the extension, execute:
pip uninstall jupyter_ai_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
Contributing
Development install
# Clone the repo to your local environment
# Change directory to the jupyter_ai_tools directory
# Install package in development mode - will automatically enable
# The server extension.
pip install -e .
You can watch the source directory and run your Jupyter Server-based application at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension. For example, when running JupyterLab:
jupyter lab --autoreload
If your extension does not depend a particular frontend, you can run the server directly:
jupyter server --autoreload
Running Tests
Install dependencies:
pip install -e ".[test]"
Development uninstall
pip uninstall jupyter_ai_tools
Packaging the extension
See RELEASE
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