Metadata-Version: 2.4
Name: earthdata_mcp_server
Version: 0.1.1
Project-URL: Home, https://github.com/datalayer/earthdata-mcp-server
Author-email: Datalayer <info@datalayer.io>
License: BSD 3-Clause License
        
        Copyright (c) 2024, Datalayer
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        ---
        
        This library reuse part of Jupyter Server code licensed under BSD 3-Clause License
        Source: https://github.com/jupyter-server/jupyter_server/blame/v2.12.0/jupyter_server/services/kernels/connection/base.py
        
        This library reuse part of traitlets code licensed under BSD 3-Clause License
        Source: https://github.com/ipython/traitlets/blob/v5.14.3/traitlets/log.py
License-File: LICENSE
Keywords: Earthdata
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: System Administrators
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.10
Requires-Dist: earthaccess
Requires-Dist: mcp[cli]>=1.2.1
Requires-Dist: rich
Provides-Extra: lint
Requires-Dist: mdformat-gfm>=0.3.5; extra == 'lint'
Requires-Dist: mdformat>0.7; extra == 'lint'
Requires-Dist: ruff; extra == 'lint'
Provides-Extra: test
Requires-Dist: ipykernel; extra == 'test'
Requires-Dist: jupyter-server<3,>=1.6; extra == 'test'
Requires-Dist: pytest>=7.0; extra == 'test'
Provides-Extra: typing
Requires-Dist: mypy>=0.990; extra == 'typing'
Description-Content-Type: text/markdown

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# 🪐 ✨ Earthdata MCP Server

[![Github Actions Status](https://github.com/datalayer/earthdata-mcp-server/workflows/Build/badge.svg)](https://github.com/datalayer/earthdata-mcp-server/actions/workflows/build.yml)
[![PyPI - Version](https://img.shields.io/pypi/v/earthdata-mcp-server)](https://pypi.org/project/earthdata-mcp-server)

Earthdata MCP Server is a [Model Context Protocol](https://modelcontextprotocol.io/introduction) (MCP) server implementation that provides tools to interact with [NASA Earth Data](https://www.earthdata.nasa.gov/). It enables efficient dataset discovery and retrieval for Geospatial 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">
    <img style="max-width:100%;" src="https://cdn.loom.com/sessions/thumbnails/c2b5b05f548d4f1492d5c107f0c48dbc-598a84f02de7e74e-full-play.gif">
  </a>
</div>

## Docker Image

```bash
# or run `docker build -t datalayer/earthdata-mcp-server .`
make build-docker
```

If you prefer, you can pull the prebuilt images.

```bash
make pull-docker
```

## Use with Claude Desktop

To use this with Claude Desktop, add the following to your `claude_desktop_config.json`.

```json
{
  "mcpServers": {
    "earthdata": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "datalayer/earthdata-mcp-server:latest"
      ]
    }
  }
}
```

> IMPORTANT
>
> You will also need the Jupyter MCP Server as documented on https://github.com/datalayer/jupyter-mcp-server.

If you are using Linux, start Claude with the following command.

```bash
make claude-linux
```

Start JupyterLab.

```bash
make jupyterlab
```

You can now prompt via Claude.

```
create an analysis about sea level rise from 2000 to 2025 in my jupyter notebook with real downloaded data
before that, install the needed python libraries you will need for the analysis
```

## Tools

The server offers 2 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.
