Earthdata MCP Server
Interact with NASA Earth Data for efficient dataset discovery and retrieval for geospatial analysis.
🪐 ✨ Earthdata MCP Server
Earthdata MCP Server is a Model Context Protocol (MCP) server implementation that provides tools to interact with NASA Earth Data.
This server is intentionally Earthdata-only.
If you need notebook/runtime tools, compose this server with jupyter-mcp-server using mcp-compose.
Key Features
- Dataset discovery on NASA Earthdata
- Granule search with temporal and bounding box filters
- Flexible download workflow with explicit execution modes
Getting Started
Local install
pip install earthdata-mcp-server
Docker with Claude Desktop
{
"mcpServers": {
"earthdata": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"datalayer/earthdata-mcp-server:latest"
],
"env": {
"EARTHDATA_USERNAME": "your_username",
"EARTHDATA_PASSWORD": "your_password"
}
}
}
}
Linux host networking
{
"mcpServers": {
"earthdata": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"--network=host",
"datalayer/earthdata-mcp-server:latest"
],
"env": {
"EARTHDATA_USERNAME": "your_username",
"EARTHDATA_PASSWORD": "your_password"
}
}
}
}
Tools
The server offers 3 Earthdata tools.
search_earth_datasets
- Search for datasets on NASA Earthdata.
- Input:
- search_keywords (str): Keywords to search for in the dataset titles.
- count (int): Number of datasets to return.
- 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: List of dataset abstracts.
search_earth_datagranules
- Search for data granules on NASA Earthdata.
- Input:
- short_name (str): Short name of the dataset.
- count (int): Number of data granules to return.
- 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: List of data granules.
download_earth_data_granules
- Search and optionally download granules with explicit modes.
- Authentication: Requires NASA Earthdata Login credentials (see authentication guide)
- Input:
- folder_name (str): Local folder name to save the data.
- short_name (str): 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).
- mode (str): One of:
manifest: Returns granule metadata only.download: Downloads files directly on server side.script: Returns Python code to execute elsewhere.
- max_manifest_items (int): Max items returned in
manifestmode.
How download works
download_earth_data_granules always starts by searching for granules with your filters, then behaves based on mode:
manifest- Returns a structured preview (
items) with IDs, titles, and links. - Does not write files.
- Best first step for validating query scope.
- Returns a structured preview (
download- Authenticates with Earthdata using environment credentials.
- Downloads matching granules directly to
folder_nameon the server runtime. - Returns downloaded file paths.
script- Returns executable Python code that performs the same search + download.
- Best option when execution should happen in a notebook/runtime controlled by another MCP server.
Recommended download strategy
- Use
mode="manifest"first to inspect results safely. - Use
mode="script"when you want notebook-driven execution viamcp-compose+jupyter-mcp-server. - Use
mode="download"only when server-side file writes are intended.
For a full composition example with mcp-compose, see download workflow docs.
Prompts
-
download_analyze_global_sea_level- Generates a workflow that starts with
download_earth_data_granulesinscriptmode. - Intended to be executed in a composed notebook/runtime stack (via
mcp-compose).
- Generates a workflow that starts with
-
sealevel_rise_dataset- Search for datasets related to sea level rise worldwide.
- Input:
start_year(int): Start year to consider.end_year(int): End year to consider.
- Returns: Prompt correctly formatted.
-
ask_datasets_format- To ask about the format of the datasets.
- Returns: Prompt correctly formatted.
Building
# or run `docker build -t datalayer/earthdata-mcp-server .`
make build-docker
If you prefer, you can pull the prebuilt images.
make pull-docker
Verwandte Server
kubeview-mcp
Read-only MCP server for AI-powered Kubernetes debugging with support of code execution
Remote MCP Server on Cloudflare
A remote MCP server deployable on Cloudflare Workers with OAuth login support, using Cloudflare KV for data storage.
Stock Market MCP Server
Provides real-time US stock market data and company financial information using the Alpha Vantage API.
Remote MCP Server (Authless)
A remote MCP server without authentication, deployable on Cloudflare Workers.
echo-mcp
Automatically convert any Echo API to a MCP Tool
Mengram
Human-like memory layer for AI agents with semantic, episodic, and procedural memory types, cognitive profiling, knowledge graph, and 12 MCP tools.
Globus
Manage research data and compute with Globus.
Remote MCP Server (Authless)
A remote, auth-less MCP server deployable on Cloudflare Workers or locally via npm.
Yandex Cloud
An unofficial server for interacting with the Yandex Cloud API.
Remote MCP Server Authless Rickroll
A remote MCP server on Cloudflare Workers that generates podcast URLs and rickrolls without authentication, using Cloudflare AI and D1.