The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Jupyter MCP Server
Model Context Protocol (MCP) Server for Jupyter.
Install
$
/plugin marketplace add datalayer/jupyter-mcp-serverInstall command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →🪐🔧 Jupyter MCP Server
An MCP server developed for AI to connect and manage Jupyter Notebooks in real-time — and scale your Code Sandbox from local to the cloud (Datalayer, Kaggle, Google Colab, Modal, Daytona, E2B, CoreWeave, Cloudflare...)
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No process to run. Datalayer now hosts this server for you at
https://mcp.datalayer.run/mcp — one endpoint for every agent and every notebook.
Sign in from your browser, approve what the agent may do, and your work keeps running
on the server after the agent disconnects.
One command to connect Claude Code, with /datalayer:notebook, /datalayer:run and
/datalayer:status on top:
/plugin marketplace add datalayer/jupyter-mcp-server
/plugin install datalayer
→ Datalayer plugin for Claude Code
Free and open source, BSD 3-Clause — point it at any Jupyter you already run, local or JupyterHub, no account needed.
Built and maintained by Datalayer, where the same server drives always-on Notebooks with GPU Code Sandboxes and durable execution — so your agent keeps working on your data when your laptop does not.
No token to copy and paste. An agent that meets this server unauthenticated is told where to authenticate, opens your browser, and you sign in to Datalayer as yourself. The agent never sees your password — it receives a token scoped to what you approved, and you can disconnect one agent without touching the others.
What each agent may do is two separate decisions: the scopes you approve
(notebooks:read, notebooks:write, code:execute, data:read) say what kind of
operation it may perform, and your own Datalayer permissions still say which notebooks it
may touch. An agent can never reach a notebook you cannot.
Personal access tokens keep working, and remain the simpler path for a CLI or a script. → OAuth and identity
Pin code-sandboxes to match your jupyter-mcp-server. The sandbox variant
jupyter was renamed to jupyter-server in code-sandboxes 1.1.1, and the two packages
have to agree on the name.
Your jupyter-mcp-server |
Install |
|---|---|
| >= 1.5.0 | code-sandboxes >= 1.1.1 |
| < 1.5.0 | code-sandboxes <= 1.0.9 |
# On 1.5.0 or later
pip install "jupyter-mcp-server>=1.5.0" "code-sandboxes>=1.1.1"
# Staying on an earlier jupyter-mcp-server
pip install "jupyter-mcp-server<1.5.0" "code-sandboxes<=1.0.9"
An older server with a newer code-sandboxes installs cleanly and then fails on the
first execution with Unknown sandbox variant: jupyter.
→ Release notes
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