Give Claude Direct Control of Your Jupyter Notebooks

Stop copying and pasting code between Claude and Jupyter. This MCP server creates a direct WebSocket bridge that lets Claude manipulate your notebooks in real-time—inserting cells, executing code, managing outputs, and even building complete presentations.

Skip the Context Switching Dance

You know the routine: ask Claude for analysis code, copy it to Jupyter, run it, paste the error back to Claude, get the fix, repeat. JupyterMCP eliminates this workflow friction by giving Claude direct access to your notebook environment.

Instead of managing two separate tools, you get a unified workflow where Claude can:

• Insert and execute cells at specific positions
• Read cell outputs and error messages directly
• Save notebooks and manage cell metadata
• Build complete presentations with proper slideshow types
• Handle both Python and statistical software like Stata

Real Productivity Gains

Complete Analysis Sessions: Ask Claude to "analyze this dataset and create visualizations comparing seaborn vs matplotlib" and watch it build the entire notebook—markdown explanations, code cells, execution, and interpretation of results.

Presentation Building: Request a technical presentation on any topic and Claude creates properly structured slides with markdown headers, code demonstrations, and appropriate cell metadata for slideshow mode.

Debugging in Context: When code fails, Claude sees the actual error output from your environment and fixes issues without the back-and-forth copy-paste cycle.

Statistical Workflows: Beyond Python, this handles Stata integration for academic and research workflows—Claude can write and execute statistical analysis code directly.

Implementation Details

The architecture uses three components working together:

• WebSocket Server: Runs inside your Jupyter session to handle notebook operations
• Client JavaScript: Manages cell manipulation and code execution within the browser
• MCP Server: Implements the Model Context Protocol to connect Claude with the WebSocket bridge

Setup requires Jupyter Notebook 6.x specifically (not JupyterLab or VS Code notebooks) and involves installing a custom kernel plus configuring Claude Desktop's MCP settings.

The connection process starts a WebSocket server in your notebook, then Claude gains access to tools like insert_and_execute_cell, get_cells_info, run_all_cells, and edit_cell_content.

When This Shines

Data Analysis Projects: Claude can execute exploratory data analysis, create visualizations, and iterate on analysis approaches without manual intervention.

Educational Content: Build complete tutorial notebooks with explanations, code examples, and proper presentation formatting.

Research Workflows: Particularly valuable for academic work involving statistical software like Stata, where Claude can handle complex analysis pipelines.

Rapid Prototyping: Skip the manual setup when testing new approaches—describe what you want and let Claude build the entire experimental notebook.

The tool includes comprehensive examples showing both Python data analysis workflows and academic statistical analysis using Stata, demonstrating the breadth of possibilities when Claude has direct notebook control.

This transforms Claude from a code assistant into a complete analysis partner that works directly within your preferred data science environment.