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jupyter-mcp-server

by datalayer

Overview

This server acts as an MCP (Model Context Protocol) adapter, allowing AI agents to connect, manage, and interact with Jupyter Notebooks in real-time, supporting dual-mode operation as a standalone server or a Jupyter extension.

Installation

Run Command
docker run -i --rm -e JUPYTER_URL='http://localhost:8888' -e JUPYTER_TOKEN='YOUR_JUPYTER_TOKEN' -e ALLOW_IMG_OUTPUT='true' datalayer/jupyter-mcp-server:latest

Environment Variables

  • PROVIDER
  • JUPYTERLAB
  • RUNTIME_URL
  • RUNTIME_ID
  • RUNTIME_TOKEN
  • DOCUMENT_URL
  • DOCUMENT_ID
  • DOCUMENT_TOKEN
  • JUPYTER_URL
  • JUPYTER_TOKEN
  • ALLOWED_JUPYTER_MCP_TOOLS
  • TRANSPORT
  • START_NEW_RUNTIME
  • PORT
  • ALLOW_IMG_OUTPUT
  • JUPYTER_MCP_SERVER_URL

Security Notes

The server's core functionality involves executing arbitrary code within a Jupyter kernel, which is a powerful operation inherent to its design. The `execute_code` and `execute_cell` tools allow running Python code and shell commands, making the server a high-privilege endpoint. Additionally, the default `FastMCPWithCORS` configuration sets `allow_origins=["*"]`, which poses a significant Cross-Origin Resource Sharing (CORS) vulnerability if the server is exposed publicly without explicitly restricting allowed origins. There are no obvious signs of obfuscation or hardcoded sensitive secrets within the provided source, but the combination of powerful execution capabilities and a permissive default CORS policy makes it risky for unhardened deployments. Users must configure CORS origins and ensure that only trusted AI agents or clients are permitted to interact with the server.

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Stats

Interest Score99
Security Score4
Cost ClassMedium
Avg Tokens500
Stars850
Forks136
Last Update2026-01-17

Tags

JupyterMCPAINotebook ManagementReal-timeCoding Agents