JupyterMCPはModel Context Protocol(MCP)を通じてJupyter NotebookとClaude AIを接続し、ClaudeがJupyter Notebookと直接やり取り・制御できるようにします。この統合により、AI支援のコード実行、データ分析、可視化などが可能になります。

⚠️ 相性警告

このツールはJupyter Notebookバージョン6.xのみに対応しています。

以下には適用されません:

• ジュピター研究所
• ジュピターノートブック v7.x
• VS Code ノートブック
• Google Colab
• その他のノートブックインターフェース

特徴

• 双方向通信:Claude AIをWebSocketベースのサーバーを介してJupyter Notebookに接続
• セル操作:ノートブックセルの挿入、実行、管理
• ノートブック管理:ノートブックの保存と情報取得
• セル実行:特定のセルを実行するか、ノートブック内のすべてのセルを実行する
• 出力取得:実行セルからテキスト制限オプション付きの出力コンテンツを取得する

構成要素

このシステムは主に3つの構成要素で構成されています。

1. WebSocket Server (jupyter_ws_server.py):Notebookと外部クライアント間の通信を橋渡しするWebSocketサーバーをJupyter内にセットアップします
2. **クライアントJavaScript ('client.

JupyterMCP - Jupyter Notebook Model Context Protocol Integration

JupyterMCP connects Jupyter Notebook to Claude AI through the Model Context Protocol (MCP), allowing Claude to directly interact with and control Jupyter Notebooks. This integration enables AI-assisted code execution, data analysis, visualization, and more.

⚠️ Compatibility Warning

This tool is compatible ONLY with Jupyter Notebook version 6.x.

It does NOT work with:

• Jupyter Lab
• Jupyter Notebook v7.x
• VS Code Notebooks
• Google Colab
• Any other notebook interfaces

Features

• Two-way communication: Connect Claude AI to Jupyter Notebook through a WebSocket-based server
• Cell manipulation: Insert, execute, and manage notebook cells
• Notebook management: Save notebooks and retrieve notebook information
• Cell execution: Run specific cells or execute all cells in a notebook
• Output retrieval: Get output content from executed cells with text limitation options

Components

The system consists of three main components:

1. WebSocket Server (jupyter_ws_server.py): Sets up a WebSocket server inside Jupyter that bridges communication between notebook and external clients
2. Client JavaScript (client.js): Runs in the notebook to handle operations (inserting cells, executing code, etc.)
3. MCP Server (jupyter_mcp_server.py): Implements the Model Context Protocol and connects to the WebSocket server

Installation

Prerequisites

• Python 3.12 or newer (probably also work with older versions, but not tested)
• uv package manager
• Claude AI desktop application

Installing uv

If you’re on Mac:

brew install uv

On Windows (PowerShell):

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

For other platforms, see the uv installation guide.

Setup

1. Clone or download this repository to your computer:

   git clone https://github.com/jjsantos01/jupyter-notebook-mcp.git
   

2. Create virtual environment with required packages an install jupyter-mcp kernel, so it can be recognized by your jupyter installation, if you had one before.

   uv run python -m ipykernel install --name jupyter-mcp
   

3. (optional) Install additional Python packages for your analysis:

   uv pip install seaborn
   

4. Configure Claude desktop integration: Go to Claude > Settings > Developer > Edit Config > claude_desktop_config.json to include the following:

      {
       "mcpServers": {
           "jupyter": {
               "command": "uv",
               "args": [
                   "--directory",
                   "/ABSOLUTE/PATH/TO/PARENT/REPO/FOLDER/src",
                   "run",