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Introduction

MCP Jupyter Server allows you to use AI assistants like Goose or Cursor to pair with you in JupyterLab notebooks where the state of your variables is preserved by the JupyterLab Kernel.

Why MCP Jupyter?​

The key advantage of MCP Jupyter is state preservation. This allows you to:

  • Work with your AI assistant in a notebook where variables and data remain intact
  • Let the AI see errors and install missing packages automatically
  • Do data exploration yourself, then hand off to the agent to continue
  • Maintain context throughout your entire session

How It Works​

MCP Jupyter acts as a bridge between MCP-compatible AI clients and your JupyterLab server:

AI Client (Goose/Cursor) <--> MCP Jupyter Server <--> JupyterLab Kernel
                                                           |
                                                      Preserved State
                                                    (Variables/Data)

This architecture ensures that your notebook state is maintained throughout the session, enabling seamless collaboration between you and your AI assistant.

Key Features​

  • State Preservation: Variables and data persist across interactions
  • Error Handling: AI can see and respond to errors in real-time
  • Package Management: Automatic package installation when needed
  • Seamless Handoff: Switch between manual and AI-assisted work anytime
  • MCP Protocol: Works with any MCP-compatible client

Next Steps​