🪐 ✨ Jupyter MCP Server

by MCP-Mirror

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About

Jupyter MCP Server is a Model Context Protocol (MCP) server that enables interaction with Jupyter notebooks running in a local JupyterLab instance. Designed for AI agents and developers, it uses Jupyter Real Time Collaboration (RTC) to reflect notebook modifications live.

Details

Author: MCP-Mirror
Downloads: 345
Categories: Search

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name 🪐 ✨ Jupyter MCP Server

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "\ud83e\ude90 \u2728 jupyter mcp server": {
            "datalayer_jupyter-mcp-server": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "datalayer/jupyter-mcp-server",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\ude90 \u2728 jupyter mcp server": {
            "datalayer_jupyter-mcp-server": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "datalayer/jupyter-mcp-server",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\ude90 \u2728 jupyter mcp server": {
            "datalayer_jupyter-mcp-server": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "datalayer/jupyter-mcp-server",
                    "."
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "\ud83e\ude90 \u2728 jupyter mcp server": {
            "datalayer_jupyter-mcp-server": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "datalayer/jupyter-mcp-server",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\ude90 \u2728 jupyter mcp server": {
            "datalayer_jupyter-mcp-server": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "datalayer/jupyter-mcp-server",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\ude90 \u2728 jupyter mcp server": {
            "datalayer_jupyter-mcp-server": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "datalayer/jupyter-mcp-server",
                    "."
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "\ud83e\ude90 \u2728 jupyter mcp server": {
            "datalayer_jupyter-mcp-server": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "datalayer/jupyter-mcp-server",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\ude90 \u2728 jupyter mcp server": {
            "datalayer_jupyter-mcp-server": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "datalayer/jupyter-mcp-server",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\ude90 \u2728 jupyter mcp server": {
            "datalayer_jupyter-mcp-server": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "datalayer/jupyter-mcp-server",
                    "."
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "\ud83e\ude90 \u2728 jupyter mcp server": {
            "datalayer_jupyter-mcp-server": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "datalayer/jupyter-mcp-server",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\ude90 \u2728 jupyter mcp server": {
            "datalayer_jupyter-mcp-server": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "datalayer/jupyter-mcp-server",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\ude90 \u2728 jupyter mcp server": {
            "datalayer_jupyter-mcp-server": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "datalayer/jupyter-mcp-server",
                    "."
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "\ud83e\ude90 \u2728 jupyter mcp server": {
            "datalayer_jupyter-mcp-server": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "datalayer/jupyter-mcp-server",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\ude90 \u2728 jupyter mcp server": {
            "datalayer_jupyter-mcp-server": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "datalayer/jupyter-mcp-server",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\ude90 \u2728 jupyter mcp server": {
            "datalayer_jupyter-mcp-server": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "datalayer/jupyter-mcp-server",
                    "."
                ]
            }
        }
    }
}

From the repository

Start JupyterLab with token authentication (jupyter lab --port 8888 --IdentityProvider.token MY_TOKEN --ip 0.0.0.0) and install the required packages (jupyterlab, jupyter-collaboration, ipykernel). Then configure the MCP client (e.g., Claude Desktop) to run the Docker image datalayer/jupyter-mcp-server:latest, setting environment variables SERVER_URL, TOKEN, and NOTEBOOK_PATH to match your JupyterLab session.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "\ud83e\ude90 \u2728 jupyter mcp server": {
            "datalayer_jupyter-mcp-server": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "datalayer/jupyter-mcp-server",
                    "."
                ]
            }
        }
    }
}

McpServers

{
    "datalayer_jupyter-mcp-server": {
        "command": "docker",
        "args": [
            "build",
            "-t",
            "datalayer/jupyter-mcp-server",
            "."
        ]
    }
}

🪐 ✨ Jupyter MCP Server

Jupyter MCP Server is a Model Context Protocol (MCP) server implementation that provides interaction with Jupyter notebooks 📓 running in a local JupyterLab 💻.

Jupyter MCP Server

Start JupyterLab

Make sure you have the following installed. The modifications made on the notebook can be seen thanks to Jupyter Real Time Collaboration (RTC).

pip install jupyterlab jupyter-collaboration ipykernel

Then, start JupyterLab with the following command:

jupyter lab --port 8888 --IdentityProvider.token MY_TOKEN --ip 0.0.0.0

> [!NOTE] > The--ip is set to 0.0.0.0 to allow the MCP server running in a Docker container to access your local JupyterLab.


Usage with Claude Desktop
To use this with Claude Desktop, add the following to your claude_desktop_config.json:

> [!IMPORTANT] > Ensure the port of theSERVER_URLand TOKEN match those used in the jupyter labcommand. > TheNOTEBOOK_PATH should be relative to the directory where JupyterLab was started.


MacOS and Windows
{
  "mcpServers": {
    "jupyter": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "SERVER_URL",
        "-e",
        "TOKEN",
        "-e",
        "NOTEBOOK_PATH",
        "datalayer/jupyter-mcp-server:latest"
      ],
      "env": {
        "SERVER_URL": "http://host.docker.internal:8888",
        "TOKEN": "MY_TOKEN",
        "NOTEBOOK_PATH": "notebook.ipynb"
      }
    }
  }
}

Linux
{
  "mcpServers": {
    "jupyter": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "SERVER_URL",
        "-e",
        "TOKEN",
        "-e",
        "NOTEBOOK_PATH",
        "--network=host",
        "datalayer/jupyter-mcp-server:latest"
      ],
      "env": {
        "SERVER_URL": "http://localhost:8888",
        "TOKEN": "MY_TOKEN",
        "NOTEBOOK_PATH": "notebook.ipynb"
      }
    }
  }
}

Components
Tools
The server currently offers 2 tools:

1. add_execute_code_cell- Add and execute a code cell in a Jupyter notebook. - Input: -cell_content(string): Code to be executed - Returns: Success message 2.add_markdown_cell- Add a markdown cell in a Jupyter notebook. - Input: -cell_content`(string): Markdown content
- Returns: Success message

Building

docker build -t datalayer/jupyter-mcp-server .

Installing via Smithery

To install Jupyter MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @datalayer/jupyter-mcp-server --client claude

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About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

🪐 ✨ Jupyter MCP Server

Start JupyterLab

Usage with Claude Desktop

MacOS and Windows

Linux

Components

Tools

Building

Installing via Smithery

Install

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