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
संबंधित सर्वर
AWS CloudTrail
This AWS Labs Model Context Protocol (MCP) server for CloudTrail enables your AI agents to query AWS account activity for security investigations, compliance auditing, and operational troubleshooting.
Multi-Cluster MCP server
A gateway for GenAI systems to interact with multiple Kubernetes clusters through the MCP.
Cloudflare MCP Server
A template for deploying a remote MCP server on Cloudflare Workers without authentication.
MemOS
MemOS (Memory Operating System) is a memory management operating system designed for AI applications.
Cisco ACI MCP Server
A comprehensive MCP server for configuring and managing Cisco ACI (Application Centric Infrastructure) fabrics through the APIC REST API.
ElevenLabs
Text-to-speech integration using the ElevenLabs API.
mcp-dropbox-sign
MCP server for the Dropbox Sign API supporting signature requests, templates, teams, accounts, events, documents, signers, reports, bulk operations, and workflows.
AniList
AniList MCP server for accessing AniList API data
Unofficial FortiMonitor MCP Server
Unofficial FortiMonitor v2 API integration exposing 241 tools across 33 modules. Covers server management, outage monitoring, maintenance windows, metrics, notifications, SNMP, cloud monitoring, dashboards, and more. Python, MIT license, Docker deployment.
CData Twitter Ads
An MCP server for accessing Twitter Ads data, powered by the CData JDBC Driver.