Overview: JupyterMCP - Jupyter Notebook Model Context Protocol Integration

Title

JupyterMCP - Jupyter Notebook Model Context Protocol Integration

How to Use

JupyterMCP connects Jupyter Notebook to Claude AI via the Model Context Protocol (MCP), enabling AI-assisted code execution, data analysis, and visualization.

Key Steps:

1. Installation:

   • Ensure Python 3.12+, uv package manager, and Claude AI desktop app are installed.
   • Clone the repository and set up the jupyter-mcp kernel.
   • Configure Claude’s claude_desktop_config.json for integration.

2. Starting the Connection:

   • Launch Jupyter Notebook (v6.x) with the jupyter-mcp kernel.
   • Initialize the WebSocket server in a notebook cell.
   • Open Claude desktop with MCP enabled.

3. Interacting with Claude:

   • Use Claude to insert, execute, and manage notebook cells via MCP tools.

Key Features

• Two-way communication between Claude AI and Jupyter Notebook.
• Cell manipulation: Insert, edit, and execute cells.
• Notebook management: Save notebooks and retrieve cell/output data.
• Multi-language support: Works with Python and Stata (via %%stata magic).

Use Cases

1. Python Data Analysis:

   • Generate Seaborn/Matplotlib visualizations.
   • Automate exploratory data analysis.

2. Stata Statistical Workflows:

   • Execute and interpret Stata code for research.

3. AI-Assisted Presentations:

   • Create dynamic slideshows with markdown explanations and live code demos.

⚠️ Note: Experimental tool—use with caution (executes arbitrary code).

For examples, see demo notebooks and video tutorials.