https://github.com/datalayer/jupyter-mcp-server
🪐 ✨ Jupyter Model Context Protocol (MCP) Server.
https://github.com/datalayer/jupyter-mcp-server
jupyter mcp-server
Last synced: 4 months ago
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🪐 ✨ Jupyter Model Context Protocol (MCP) Server.
- Host: GitHub
- URL: https://github.com/datalayer/jupyter-mcp-server
- Owner: datalayer
- License: other
- Created: 2025-02-12T06:41:35.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-02-28T14:35:41.000Z (4 months ago)
- Last Synced: 2025-02-28T15:06:39.500Z (4 months ago)
- Topics: jupyter, mcp-server
- Language: Python
- Homepage: https://datalayer.io
- Size: 92.8 KB
- Stars: 8
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
- mcp-index - Jupyter MCP Server - Interact with Jupyter notebooks in a local JupyterLab environment, enabling the addition and execution of code or markdown cells. (Education and Learning)
README
[](https://datalayer.io)
[](https://github.com/sponsors/datalayer)
# 🪐 ✨ Jupyter MCP Server
[](https://github.com/datalayer/jupyter-mcp-server/actions/workflows/build.yml)
[](https://pypi.org/project/jupyter-mcp-server)
[](https://smithery.ai/server/@datalayer/jupyter-mcp-server)
Jupyter MCP Server is a [Model Context Protocol](https://modelcontextprotocol.io/introduction) (MCP) server implementation that provides interaction with Jupyter notebooks 📓 running in a local JupyterLab 💻.
## Start JupyterLab
Make sure you have the following installed. The modifications made on the notebook can be seen thanks to [Jupyter Real Time Collaboration](https://jupyterlab.readthedocs.io/en/stable/user/rtc.html) (RTC).
```bash
pip install jupyterlab jupyter-collaboration ipykernel
```
Then, start JupyterLab with the following command:
```bash
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 the `SERVER_URL`and `TOKEN` match those used in the `jupyter lab` command.
> The `NOTEBOOK_PATH` should be relative to the directory where JupyterLab was started.
### MacOS and Windows
```json
{
"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
```json
{
"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 3 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: Cell output.
2. `add_markdown_cell`
- Add a markdown cell in a Jupyter notebook.
- Input:
- `cell_content`(string): Markdown content.
- Returns: Success message.
3. `download_earth_data_granules`
⚠️ We plan to migrate this tool to a separate repository in the future as it is specific to Geospatial analysis.
- Add a code cell in a Jupyter notebook to download Earth data granules from NASA Earth Data.
- Input:
- `folder_name`(string): Local folder name to save the data.
- `short_name`(string): Short name of the Earth dataset to download.
- `count`(int): Number of data granules to download.
- `temporal` (tuple): (Optional) Temporal range in the format (date_from, date_to).
- `bounding_box` (tuple): (Optional) Bounding box in the format (lower_left_lon, lower_left_lat, upper_right_lon, upper_right_lat).
- Returns: Cell output.
## Building
```bash
docker build -t datalayer/jupyter-mcp-server .
```
## Installing via Smithery
To install Jupyter MCP Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@datalayer/jupyter-mcp-server):
```bash
npx -y @smithery/cli install @datalayer/jupyter-mcp-server --client claude
```