Enables exporting processed satellite imagery and analysis results from Google Earth Engine directly to Google Cloud Storage buckets
Provides comprehensive tools for satellite imagery analysis including dataset searching, image filtering by date and location, NDVI calculation, map visualization, and statistical analysis of Earth observation data
Earth Engine MCP Server
A Model Context Protocol (MCP) server for Google Earth Engine that enables satellite imagery analysis through Claude Desktop or any MCP-compatible client.
๐ Quick Start
Prerequisites
Google Earth Engine Account: Sign up at earthengine.google.com
Service Account Key: Create a service account in Google Cloud Console with Earth Engine API access
Node.js: Version 18 or higher
Google Cloud Storage Permissions (for exports): See GCS Permissions Guide
Installation
Configuration
Download your Earth Engine service account JSON key from Google Cloud Console
Save it to a secure location (e.g.,
C:\Users\YourName\ee-key.json
)
๐ง Usage
Option 1: Claude Desktop (Recommended)
Edit Claude Desktop configuration:
Open
%APPDATA%\Claude\claude_desktop_config.json
and add:{ "mcpServers": { "earth-engine": { "command": "node", "args": ["C:\\path\\to\\earth-engine-mcp\\mcp-earth-engine.js"], "env": { "EARTH_ENGINE_PRIVATE_KEY": "C:\\path\\to\\your\\ee-key.json" } } } }Restart Claude Desktop
Use Earth Engine tools in Claude:
"Search for Sentinel-2 datasets"
"Calculate NDVI for San Francisco"
"Get Landsat imagery for January 2024"
Option 2: Direct MCP Client
Option 3: SSE Endpoint (For Web Clients)
๐ Available Tools
1. search_catalog
Search the Earth Engine data catalog for datasets.
2. get_band_names
Get available bands for a dataset.
3. filter_collection
Filter satellite imagery by date and location.
4. calculate_ndvi
Calculate Normalized Difference Vegetation Index.
5. get_map_url
Generate map visualization URLs.
6. calculate_statistics
Calculate image statistics for a region.
7. export_image_to_cloud_storage ๐
Export satellite imagery to Google Cloud Storage (works with service accounts).
Note: Service accounts cannot export to Google Drive. Use GCS exports instead. See GCS Permissions Guide for setup instructions.
๐งช Testing
๐ Example Workflows
NDVI Analysis for Agriculture
Deforestation Monitoring
Urban Heat Island Analysis
๐ Supported Datasets
Sentinel-2: High-resolution optical imagery (10m)
Landsat 8/9: Multispectral imagery (30m)
MODIS: Daily global coverage
CHIRPS: Precipitation data
SRTM: Digital elevation models
And many more in the Earth Engine catalog
๐ Security
Never commit your service account key to version control
Store keys in secure locations with restricted access
Use environment variables for production deployments
Rotate service account keys regularly
๐ค Contributing
Contributions are welcome! Please:
Fork the repository
Create a feature branch
Add tests for new features
Submit a pull request
๐ License
MIT License - See LICENSE file for details
๐ Troubleshooting
"Earth Engine not initialized"
Check your service account key path
Verify the key has Earth Engine API access
Ensure the project has Earth Engine API enabled
"Dataset not found"
Use the exact dataset ID from Earth Engine catalog
Check if the dataset requires special access
Connection issues
Verify Node.js version (18+)
Check firewall settings
Ensure all dependencies are installed
๐ง Support
GitHub Issues: github.com/Dhenenjay/earth-engine-mcp/issues
Earth Engine Documentation: developers.google.com/earth-engine
๐ Quick Test
After setup, try this in Claude Desktop:
"Search for Sentinel-2 satellite imagery and calculate NDVI for San Francisco in January 2024"
The server will:
Search the Earth Engine catalog
Filter Sentinel-2 data for the specified time and location
Calculate NDVI vegetation index
Return statistics and visualization URLs
Happy Earth Observing! ๐ฐ๏ธ
This server cannot be installed
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
Enables satellite imagery analysis through Google Earth Engine, allowing users to search datasets, calculate vegetation indices like NDVI, filter collections by location and date, and export imagery to cloud storage. Supports major satellite datasets including Sentinel-2, Landsat, and MODIS for applications like agriculture monitoring and deforestation tracking.