https://github.com/datalayer/jupyter-earth-mcp-server
🪐 🌎 Jupyter Earth MCP Server
https://github.com/datalayer/jupyter-earth-mcp-server
earth esa jupyter mcp mcp-server nasa
Last synced: 4 months ago
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🪐 🌎 Jupyter Earth MCP Server
- Host: GitHub
- URL: https://github.com/datalayer/jupyter-earth-mcp-server
- Owner: datalayer
- License: bsd-3-clause
- Created: 2025-04-09T07:51:03.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2025-05-20T10:37:23.000Z (6 months ago)
- Last Synced: 2025-06-21T01:52:53.841Z (5 months ago)
- Topics: earth, esa, jupyter, mcp, mcp-server, nasa
- Language: Python
- Homepage: https://datalayer.ai
- Size: 21.5 KB
- Stars: 3
- Watchers: 1
- Forks: 4
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
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README
[](https://datalayer.io)
[](https://github.com/sponsors/datalayer)
# 🌎 ✨ Jupyter Earth MCP Server
[](https://github.com/datalayer/jupyter-earth-mcp-server/actions/workflows/build.yml)
[](https://pypi.org/project/jupyter-earth-mcp-server)
🌍 Jupyter Earth MCP Server is a [Model Context Protocol](https://modelcontextprotocol.io) (MCP) server implementation that provides a set of tools for 🗺️ Geospatial analysis in 📓 Jupyter notebooks.
The following demo uses the [Earthdata MCP server](https://github.com/datalayer/earthdata-mcp-server) to search for datasets and data granules on NASA Earthdata, this MCP server to download the data in Jupyter and the [jupyter-mcp-server](https://github.com/datalayer/jupyter-mcp-server) to run further analysis.
## Start JupyterLab
Make sure you have the following installed. The collaboration package is needed as the modifications made on the notebook can be seen thanks to [Jupyter Real Time Collaboration](https://jupyterlab.readthedocs.io/en/stable/user/rtc.html).
```bash
pip install jupyterlab==4.4.1 jupyter-collaboration==4.0.2 ipykernel
pip uninstall -y pycrdt datalayer_pycrdt
pip install datalayer_pycrdt==0.12.17
```
Then, start JupyterLab with the following command.
```bash
jupyter lab --port 8888 --IdentityProvider.token MY_TOKEN --ip 0.0.0.0
```
You can also run `make jupyterlab`.
> [!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.
## Use with Claude Desktop
Claude Desktop can be downloaded [from this page](https://claude.ai/download) for macOS and Windows.
For Linux, we had success using this [UNOFFICIAL build script based on nix](https://github.com/k3d3/claude-desktop-linux-flake)
```bash
# ⚠️ UNOFFICIAL
# You can also run `make claude-linux`
NIXPKGS_ALLOW_UNFREE=1 nix run github:k3d3/claude-desktop-linux-flake \
--impure \
--extra-experimental-features flakes \
--extra-experimental-features nix-command
```
To use this with Claude Desktop, add the following to your `claude_desktop_config.json` (read more on the [MCP documentation website](https://modelcontextprotocol.io/quickstart/user#2-add-the-filesystem-mcp-server)).
> [!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.
### Claude Configuration on macOS and Windows
```json
{
"mcpServers": {
"jupyter-earth": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"SERVER_URL",
"-e",
"TOKEN",
"-e",
"NOTEBOOK_PATH",
"datalayer/jupyter-earth-mcp-server:latest"
],
"env": {
"SERVER_URL": "http://host.docker.internal:8888",
"TOKEN": "MY_TOKEN",
"NOTEBOOK_PATH": "notebook.ipynb"
}
}
}
}
```
### Claude Configuration on Linux
```bash
CLAUDE_CONFIG=${HOME}/.config/Claude/claude_desktop_config.json
cat < $CLAUDE_CONFIG
{
"mcpServers": {
"jupyter-earth": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"SERVER_URL",
"-e",
"TOKEN",
"-e",
"NOTEBOOK_PATH",
"--network=host",
"datalayer/jupyter-earth-mcp-server:latest"
],
"env": {
"SERVER_URL": "http://localhost:8888",
"TOKEN": "MY_TOKEN",
"NOTEBOOK_PATH": "notebook.ipynb"
}
}
}
}
EOF
cat $CLAUDE_CONFIG
```
## Components
### Tools
The server currently offers 1 tool:
1. `download_earth_data_granules`
- 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.
### Prompts
1. `download_analyze_global_sea_level`
- To ask for downloading and analyzing global sea level data in Jupyter.
- Returns: Prompt correctly formatted.
## Building
You can build the Docker image it from source.
```bash
make build-docker
```
