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Quickstart

Get up and running with MCP Jupyter in minutes.

Requirements​

  • UV - Required for installation
  • JupyterLab with jupyter-collaboration and ipykernel
  • An MCP-compatible client (e.g., Goose, Cursor)

Installation​

MCP Jupyter Server uses stdio and can be added to any MCP client with:

uvx mcp-jupyter

Quick Setup​

1. Start Jupyter Server​

First, set up and start your Jupyter server:

# Create virtual environment
uv venv
source .venv/bin/activate

# Install dependencies
uv pip install jupyterlab jupyter-collaboration ipykernel

# Start Jupyter server
jupyter lab --port 8888 --IdentityProvider.token BLOCK --ip 0.0.0.0
tip

The server expects a token for authentication. If the TOKEN environment variable is not set, it defaults to "BLOCK".

2. Configure Your MCP Client​

For Goose​

Add MCP Jupyter to your Goose configuration:

goose session --with-extension "uvx mcp-jupyter"

For Other Clients​

Add the following to your MCP client configuration:

{
  "mcpServers": {
    "jupyter": {
      "command": "uvx",
      "args": ["mcp-jupyter"]
    }
  }
}

3. Start Using​

Once configured, you can:

  1. Create or open a notebook through your AI assistant
  2. Execute code cells with preserved state
  3. Let the AI handle errors and install packages
  4. Switch between manual and AI-assisted work seamlessly

Example Session​

# Your AI assistant can help you:
# 1. Load and explore data
# 2. Visualize results
# 3. Debug errors
# 4. Install missing packages
# All while preserving your notebook state!

Next Steps​