$ loading_
Analyze H3 spatial data for pricing, indicators, geometry, and concordance.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "com.htagai/htag-spatial" MCP server from askskill: Run: claude mcp add --transport http 'com-htagai-htag-spatial' 'https://api.htagai.com/mcp/v1/servers/htag-spatial/mcp'
Use this tool to aggregate neighborhood rent data by H3 cells and identify high-rent hotspots.
A grid-based rent distribution, hotspot list, and brief conclusions.
Compare two cities across H3 levels for population density, housing prices, and commute indicators.
A multi-level indicator comparison table with a difference summary.
Convert these administrative boundary geometries into H3 cells and generate a concordance to the original مناطق.
Geometry conversion results, H3 cell list, and concordance mapping.
Enable geospatial search, routing, and map analytics for location-aware applications.
Manage projects, track issues, and collaborate in Huly using natural language.
Run and manage H agents directly from any MCP client.
Search open government geospatial data and query ArcGIS Feature Services.
Query India's open geospatial data with location, filtering, and nearby search.
Give AI agents persistent memory with search, tags, and importance ranking.