Developer Tools
Connect to Terrascout from your AI assistant (MCP), terminal (CLI), or automate with the Skills Engine. All methods access the same geospatial intelligence engine.
Available Tools
Describe a project in plain English and get matched satellite/spatial data sources with fit scores.
scope_geospatial_dataQuick viability assessment — sensor options, detection confidence, and caveats.
get_feasibilityHistorical monthly cloud cover for any location. Powered by Open-Meteo.
get_cloud_coverSearch STAC catalogs for recent satellite scenes over a bounding box.
preview_satellite_dataBrowse the provider catalog — filter by type, resolution, or free-only.
search_providersGenerate a PDF compliance report from a saved scope.
generate_scope_reportDiscover all available geospatial data for an area of interest — fires, earthquakes, climate, DEM, and more.
discover_area_dataQuick Setup
{
"mcpServers": {
"terrascout": {
"url": "https://terrascout.app/mcp/"
}
}
}Save as .mcp.json in your project root, then restart Claude Code.
Try It
After setup, try these prompts with your AI assistant:
“Check cloud cover for Melbourne at lat -37.81, lon 144.96 for the last 12 months.”
“Find the best satellite data for monitoring vegetation on a 500ha mine site near Emerald QLD.”
“Show me all free optical sensors with resolution under 10 meters.”
“Is it feasible to detect illegal land clearing in tropical Queensland?”
How It Works
AI Assistant (Claude / Cursor / Windsurf)
│
├── stdio ──────→ python -m backend.app.mcp.server (local)
│
└── HTTP ───────→ http://localhost:4174/mcp/
│
└── FastAPI ──→ FastMCP (7 tools)
│
├── scope_geospatial_data → Matching Engine
├── get_feasibility → Matching + Cloud Cover
├── get_cloud_cover → Open-Meteo API
├── preview_satellite_data → STAC Catalogs
├── search_providers → PostgreSQL / PostGIS
├── generate_scope_report → PDF Generator
└── discover_area_data → Data Catalog