google-earth-engine-mcp

cameronking4/google-earth-engine-mcp

3.3

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This document provides a comprehensive overview of the Google Earth Engine MCP Server, which utilizes the Vercel MCP Adapter to integrate MCP server capabilities into Next.js projects.

The Google Earth Engine MCP Server is a robust solution designed to facilitate geospatial analysis through the integration of Google Earth Engine tools within a Next.js framework. By leveraging the Vercel MCP Adapter, developers can seamlessly incorporate MCP server functionalities into their applications, enabling advanced geospatial data processing and visualization. This server setup is particularly beneficial for AI assistants that require access to Earth Engine datasets for tasks such as data visualization, statistics computation, and dataset search. The server is optimized for deployment on Vercel, with specific configurations for efficient execution, including the use of Fluid compute and Redis for SSE transport. This setup ensures that applications can handle complex geospatial queries and deliver results efficiently.

Features

  • Integration with Google Earth Engine for geospatial analysis
  • Utilizes Vercel MCP Adapter for seamless Next.js integration
  • Supports visualization and computation of Earth Engine datasets
  • Optimized for deployment on Vercel with Fluid compute
  • Includes sample client for testing invocations

Usages

usage with Vercel

To use the SSE transport, requires a Redis attached to the project under `process.env.REDIS_URL`
Make sure you have [Fluid compute](https://vercel.com/docs/functions/fluid-compute) enabled for efficient execution
After enabling Fluid compute, open `app/route.ts` and adjust `maxDuration` to 60 (or higher if using a Vercel Pro or Enterprise account)
[Deploy the Next.js MCP template](https://vercel.com/templates/next.js/model-context-protocol-mcp-with-next-js)

usage with Google Earth Engine

This project includes MCP tools for interacting with Google Earth Engine, a cloud-based platform for geospatial analysis. These tools allow AI assistants to:

- Initialize and authenticate with Earth Engine
- Visualize Earth Engine datasets as maps
- Retrieve information about Earth Engine datasets
- Compute statistics for Earth Engine data in specified regions
- Search for Earth Engine datasets

To use Earth Engine tools, you'll need:
1. A Google Earth Engine account
2. A Google Cloud service account with Earth Engine access
3. A service account private key for authentication

usage with Next js

This sample app uses the [Vercel MCP Adapter](https://www.npmjs.com/package/@vercel/mcp-adapter) that allows you to drop in an MCP server on a group of routes in any Next.js project.

Update `app/[transport]/route.ts` with your tools, prompts, and resources following the [MCP TypeScript SDK documentation](https://github.com/modelcontextprotocol/typescript-sdk/tree/main?tab=readme-ov-file#server).

Tools

  1. Initialize and authenticate with Earth Engine

    Allows AI assistants to establish a connection with Google Earth Engine.

  2. Visualize Earth Engine datasets as maps

    Enables the rendering of geospatial data on maps for better analysis.

  3. Retrieve information about Earth Engine datasets

    Provides detailed metadata and information about available datasets.

  4. Compute statistics for Earth Engine data in specified regions

    Facilitates statistical analysis of geospatial data within defined areas.

  5. Search for Earth Engine datasets

    Allows users to find specific datasets within the Earth Engine catalog.