🪐 ✨ Jupyter MCP Server

Name: 🪐 ✨ Jupyter MCP Server
Author: MCP-Mirror

@MCP-Mirror

リポジトリ

🪐 ✨ Jupyter MCP Server について

Mirror of

#jupyter #mcp-server #data-science

基本情報

カテゴリ

データと分析

トランスポート

stdio

公開者

MCP-Mirror

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "datalayer_jupyter-mcp-server": {
      "command": "docker",
      "args": [
        "build",
        "-t",
        "datalayer/jupyter-mcp-server",
        "."
      ]
    }
  }
}

ツール

`cell_content`(string): Code to be executed

Success message

`cell_content`(string): Markdown content

Success message

概要

What is Jupyter MCP Server?

Jupyter MCP Server is a Model Context Protocol (MCP) server that enables interaction with Jupyter notebooks running in a local JupyterLab instance. Designed for AI agents and developers, it uses Jupyter Real Time Collaboration (RTC) to reflect notebook modifications live.

How to use Jupyter MCP Server?

Start JupyterLab with token authentication (jupyter lab --port 8888 --IdentityProvider.token MY_TOKEN --ip 0.0.0.0) and install the required packages (jupyterlab, jupyter-collaboration, ipykernel). Then configure the MCP client (e.g., Claude Desktop) to run the Docker image datalayer/jupyter-mcp-server:latest, setting environment variables SERVER_URL, TOKEN, and NOTEBOOK_PATH to match your JupyterLab session.

Key features of Jupyter MCP Server

Connect AI agents to live Jupyter notebooks
Add and execute code cells remotely
Insert Markdown cells into notebooks
Uses Docker for easy deployment
Works with JupyterLab’s Real Time Collaboration

Use cases of Jupyter MCP Server

Enable a language model to run Python code in a Jupyter notebook
Automatically generate and insert analysis cells with results
Combine AI-generated explanations with computed outputs in a single notebook

FAQ from Jupyter MCP Server

What tools does Jupyter MCP Server offer?

Two tools: add_execute_code_cell (executes Python code and returns success) and add_markdown_cell (adds Markdown content). Both take a cell_content string.

What are the runtime dependencies?

A local JupyterLab with jupyter-collaboration and ipykernel installed, plus Docker to run the MCP server container.

How do I authenticate to my JupyterLab instance?

You must set a token via --IdentityProvider.token MY_TOKEN when starting JupyterLab, then provide the same token in the TOKEN environment variable in the MCP client configuration.

How does the server connect to a running JupyterLab?

The SERVER_URL environment variable (e.g., http://localhost:8888) tells the Docker container where JupyterLab is listening. On Linux, the --network=host Docker flag is used; on macOS/Windows, the container accesses the host via host.docker.internal.