Jupyter_MCP_Server

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.

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:

WebSocket Server (jupyter_ws_server.py): Sets up a WebSocket server inside Jupyter that bridges communication between notebook and external clients
Client JavaScript (client.js): Runs in the notebook to handle operations (inserting cells, executing code, etc.)
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

Clone or download this repository to your computer:

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

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
```
(optional) Install additional Python packages for your analysis:
```
uv pip install seaborn
```

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",
                "jupyter_mcp_server.py"
            ]
        }
    }
}

Replace /ABSOLUTE/PATH/TO/ with the actual path to the src folder on your system. For example:

Windows: "C:\\Users\\MyUser\\GitHub\\jupyter-notebook-mcp\\src\\"
Mac: /Users/MyUser/GitHub/jupyter-notebook-mcp/src/

If you had previously opened Claude, then File > Exit and open it again.

Usage

Starting the Connection

Start your Jupyter Notebook (version 6.x) server:
```
uv run jupyter nbclassic
```
Create a new Jupyter Notebook and make sure that you choose the jupyter-mcp kernel: kernel -> change kernel -> jupyter-mcp
In a notebook cell, run the following code to initialize the WebSocket server:
```
import sys
sys.path.append('/path/to/jupyter-notebook-mcp/src')  # Add the path to where the scripts are located

from jupyter_ws_server import setup_jupyter_mcp_integration

# Start the WebSocket server inside Jupyter
server, port = setup_jupyter_mcp_integration()
```
Don't forget to replace here '/path/to/jupyter-notebook-mcp/src' with src folder on your system. For example:
- Windows: "C:\\Users\\MyUser\\GitHub\\jupyter-notebook-mcp\\src\\"
- Mac: /Users/MyUser/GitHub/jupyter-notebook-mcp/src/
Notebook setup
Launch Claude desktop with MCP enabled.

Using with Claude

Once connected, Claude will have access to the following tools:

ping - Check server connectivity
insert_and_execute_cell - Insert a cell at the specified position and execute it
save_notebook - Save the current Jupyter notebook
get_cells_info - Get information about all cells in the notebook
get_notebook_info - Get information about the current notebook
run_cell - Run a specific cell by its index
run_all_cells - Run all cells in the notebook
get_cell_text_output - Get the output content of a specific cell
get_image_output - Get the images output of a specific cell
edit_cell_content - Edit the content of an existing cell
set_slideshow_type- Set the slide show type for cell