Earthdata MCP Server

Interact with NASA Earth Data for efficient dataset discovery and retrieval for geospatial analysis.

Datalayer

Become a Sponsor

🪐 ✨ Earthdata MCP Server

PyPI - Version smithery badge Unit Tests Lint and Type Check

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 manifest mode.

How download works

download_earth_data_granules always starts by searching for granules with your filters, then behaves based on mode:

  1. manifest
    • Returns a structured preview (items) with IDs, titles, and links.
    • Does not write files.
    • Best first step for validating query scope.
  2. download
    • Authenticates with Earthdata using environment credentials.
    • Downloads matching granules directly to folder_name on the server runtime.
    • Returns downloaded file paths.
  3. 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

  1. Use mode="manifest" first to inspect results safely.
  2. Use mode="script" when you want notebook-driven execution via mcp-compose + jupyter-mcp-server.
  3. Use mode="download" only when server-side file writes are intended.

For a full composition example with mcp-compose, see download workflow docs.

Prompts

  1. download_analyze_global_sea_level

    • Generates a workflow that starts with download_earth_data_granules in script mode.
    • Intended to be executed in a composed notebook/runtime stack (via mcp-compose).
  2. 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.
  3. 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

Serveurs connexes