What is Mcp Server Jupyter

mcp-server-jupyter is an MCP server designed for managing and interacting with Jupyter notebooks programmatically, allowing users to manipulate notebook content and execute cells efficiently.

Use cases

Use cases for mcp-server-jupyter include automated notebook management, programmatic interaction with Jupyter notebooks, and integration with other applications for enhanced data analysis and visualization workflows.

How to use

To use mcp-server-jupyter, first start JupyterLab or Jupyter Notebook using the uv tool. Then, configure your Claude Desktop by adding the necessary command and environment variables to the config file. Finally, open or create a notebook and interact with it through Claude Desktop by using the full path to the notebook.

Key features

Key features include tools for reading notebook content with or without outputs, reading specific cell outputs, adding new cells, modifying existing cells, and executing cells to retrieve outputs.

Where to use

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mcp-server-jupyter

An MCP server for managing and interacting with Jupyter notebooks programmatically.

Components

Tools

The server provides six tools for notebook manipulation:

1. read_notebook_with_outputs: Read a notebook’s content including cell outputs

   • Required: notebook_path (string)

2. read_notebook_source_only: Read notebook content without outputs

   • Required: notebook_path (string)
   • Use when size limitations prevent reading full notebook with outputs

3. read_output_of_cell: Read output of a specific cell

   • Required:
     • notebook_path (string)
     • cell_id (string)

4. add_cell: Add new cell to notebook

   • Required:
     • notebook_path (string)
     • source (string)
   • Optional:
     • cell_type (string): “code” or “markdown”
     • position (integer): insertion index (-1 to append)

5. edit_cell: Modify existing cell content

   • Required:
     • notebook_path (string)
     • cell_id (string): Unique ID of the cell to edit
     • source (string)

6. execute_cell: Execute a specific cell and return its output

   • Required:
     • notebook_path (string)
     • cell_id (string)
   • Useful for verifying cell execution and output

Usage with Claude Desktop

Step1: Start JupyterLab or Jupyter Notebook

By using uv to run Jupyter notebooks it’s much easier to manage venv and package installations.

Follow uv jupyter docummentation for more details.

uv venv --seed
source .venv/bin/activate
uv pip install jupyterlab
.venv/bin/jupyter lab

NOTE: this environment should be used as UV_PROJECT_ENVIRONMENT env variable in MCP server (next step). Run in the same folder where Jupyter started.

echo $(pwd)/.venv

Step2: Configure Claude Desctop Add this configuration to your Claude Desktop config file:

PyPi package:

Git repo fork

Step 3: Open Notebook & Claude Chat

Open or create a notebook in JupyterLab/Jupyter Notebook

Get the full path to your notebook:

• In JupyterLab: Right-click on the notebook in the file browser → “Copy Path”
• In Jupyter Notebook: Copy the path from the URL (modify to full system path)

In Claude Desktop chat:

• Always use the full path to the notebook when calling tools
• Example: /Users/username/projects/my_notebook.ipynb

Important Notes:

• After any modifications through Claude (add_cell, edit_cell):
  • Reload the notebook page in JupyterLab/Jupyter Notebook
  • Current version does not support automatic reload
• Keep JupyterLab/Jupyter Notebook instance running while working with Claude

License

This project is licensed under the MIT License. See the LICENSE file for details.