JupyterLab Collab MCP

Give AI assistants full access to your Jupyter notebooks — read, edit, execute, and collaborate in real-time.

Claude Code  ←—stdio—→  MCP Server  ←—y-websocket—→  JupyterLab

Why?

Claude Code can already edit files, but notebooks are special — they have cells, kernels, outputs, and a live browser UI. This MCP server bridges the gap:

• Real-time sync — edits appear instantly in JupyterLab via y-websocket
• 53 tools — read, edit, execute, search, diff, tag, lock, snapshot, and more
• Cell ID addressing — stable references that survive insertions and deletions
• Multi-agent ready — cell locking, change tracking, and per-agent attribution
• Context-efficient — filter by cell type, skip outputs, limit images
• No extension needed — uses JupyterLab's built-in jupyter-collaboration

Install

With npx (recommended)

Requires Node.js 18+. No cloning or building needed:

claude mcp add -s user jupyter -- npx jupyterlab-collab-mcp

That's it. npx downloads and caches the package automatically.

With uvx (no Node.js required)

If you don't have Node.js installed, the deno PyPI package bundles Deno — a JavaScript runtime with built-in npm compatibility:

claude mcp add -s user jupyter -- uvx deno -A npm:jupyterlab-collab-mcp

From source (development)

git clone https://github.com/ianhi/jupyterlab-collab-mcp.git
cd jupyterlab-collab-mcp
npm install && npm run build
claude mcp add -s user jupyter -- node $PWD/dist/index.js

Usage

1. Start JupyterLab with jlabx (or jupyter lab if you already have jupyter-collaboration installed)
2. In Claude Code: "Connect to http://localhost:8888/lab?token=..."
3. Ask Claude to read, edit, or run cells

Most tools also work without a JupyterLab connection by reading/writing .ipynb files directly (no kernel operations in this mode).

jlabx launcher

jlabx launches JupyterLab with all the right extensions (collaboration, LSP, vim, MyST, git) without modifying your project dependencies.

uv tool install jlabx
jlabx

Documentation

Full docs: https://ianhi.github.io/jupyterlab-collab-mcp/

The docs site has detailed tool reference pages, parameter tables, examples, and guides for multi-agent collaboration.

Related Projects

See also datalayer/jupyter-mcp-server — a Python-based alternative with Streamable HTTP transport and streaming execution. See the comparison page for detailed differences.

License

BSD-3-Clause