download_earth_data_granulesLABSCO SUMMARY
Read the first line before you install it.
The repository is archived and names its successor, so start at earthdata-mcp-server rather than here. What remains interesting is the pattern: the download lands in the notebook as a real cell, which means the fetch is reproducible by whoever opens the notebook next instead of being a side effect of a chat session.
What it is
An MCP server that writes a download cell into a live JupyterLab notebook and runs it, pulling Earth data granules from NASA Earthdata onto the machine where the notebook lives. The repository is archived: its first line directs you to https://github.com/datalayer/earthdata-mcp-server.
What you get
download_earth_data_granules— adds and runs a code cell that fetches granules, takingfolder_namefor where to save,short_namefor the dataset,countfor how many, and optionaltemporalandbounding_boxtuples to narrow the request- A prompt,
download_analyze_global_sea_level, that frames the download-and-analyze task for you - Cell output returned to the conversation, so the assistant sees what the download actually did
Requirements
A running JupyterLab with real-time collaboration installed, so edits made to the notebook are visible: jupyterlab==4.4.1, jupyter-collaboration==4.0.2, ipykernel and datalayer_pycrdt==0.12.17. Start it with jupyter lab --port 8888 --IdentityProvider.token MY_TOKEN --ip 0.0.0.0 — the wide bind is what lets the containerized server reach it. The client runs the datalayer/jupyter-earth-mcp-server:latest image with SERVER_URL, TOKEN and NOTEBOOK_PATH, the last relative to where JupyterLab started. BSD 3-Clause.
Setup effort
One command — docker run -i --rm -e SERVER_URL -e TOKEN -e NOTEBOOK_PATH datalayer/jupyter-earth-mcp-server:latest
USE CASES
01
Getting satellite data into a notebook without leaving the conversation
Name the dataset, the count and a bounding box, and the download cell is written and run for you.
02
Starting a sea level analysis
Use the bundled prompt, which frames the download and the analysis together instead of leaving you to phrase it.
03
Keeping the fetch reproducible
Because the download is a notebook cell, the next person to open the notebook can re-run it exactly.
1 tool
Listed in project docs. Your client may show a different list.
BEFORE YOU INSTALL
What to know first
Tools you get
1 tool named in the project's documentation.
Requires
docker on PATH
Where it runs
Both documented setups run the server on your machine.
INSTALLATION
Connect your client
Server setup
TERMINAL
docker run -i --rm -e SERVER_URL -e TOKEN -e NOTEBOOK_PATH datalayer/jupyter-earth-mcp-server:latestMCP Clients
Claude Desktop — macOS, Windows
CLAUDE DESKTOP — MACOS, 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": "<YOUR_TOKEN>",
"NOTEBOOK_PATH": "notebook.ipynb"
}
}
}
}Claude Desktop — Linux
CLAUDE DESKTOP — LINUX · JSON
{
"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": "<YOUR_TOKEN>",
"NOTEBOOK_PATH": "notebook.ipynb"
}
}
}
}
