🌎 ✨ Jupyter Earth MCP Server
About
Jupyter Earth MCP Server is a Model Context Protocol (MCP) server implementation that provides geospatial analysis tools for Jupyter notebooks, enabling download of NASA Earth data granules.
Details
- License
- BSD-3-Clause license
Explore
- One tool: download_earth_data_granules
- One prompt: download_analyze_global_sea_level
- Runs as a Docker container
- Integrates with Claude Desktop
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 Earth MCP ServerCommand (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
From the repository
{
"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_CONFIG=${HOME}/.config/Claude/claude_desktop_config.json
cat <<EOF > $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
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).
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.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"\ud83c\udf0e \u2728 jupyter earth mcp server": {
"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": "",
"TOKEN": "",
"NOTEBOOK_PATH": ""
}
}
}
}
}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": "",
"TOKEN": "",
"NOTEBOOK_PATH": ""
}
}
}
🌍 Jupyter Earth MCP Server is a Model Context Protocol (MCP) server implementation that provides a set of tools for 🗺️ Geospatial analysis in 📓 Jupyter notebooks.
The following demo uses the 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 to run further analysis.
<div>
<a href="https://www.loom.com/share/c2b5b05f548d4f1492d5c107f0c48dbc">
<p>Analyzing Sea Level Rise with AI-Powered Geospatial Tools and Jupyter - Watch Video</p>
</a>
<a href="https://www.loom.com/share/c2b5b05f548d4f1492d5c107f0c48dbc">
</a>
</div>
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.
pip install jupyterlab==4.4.1 jupyter-collaboration==4.0.2 ipykernel
pip uninstall -y pycrdt datalayer_pycrdt
pip install datalayer_pycrdt==0.12.15
Then, start JupyterLab with the following command.
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 for macOS and Windows.
For Linux, we had success using this UNOFFICIAL build script based on nix
```bash
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