MCP Server for Sentinel-1 PSETAE

Example Use Cases

• 1

  Retrieve and process Sentinel-1 satellite data via Google Earth Engine.

• 2

  Train and tune PSETAE models for crop classification.

• 3

  Perform inference and generate crop classification maps using trained models.

Description

This MCP server implements a multi-agent system using the Model Context Protocol to orchestrate crop classification workflows based on Sentinel-1 satellite imagery. It integrates with Google Earth Engine for data extraction and leverages the PSETAE model for training and inference. The modular agent design enables efficient workflow automation from data retrieval to coverage analysis, providing a stable baseline for Sentinel-1 data processing.