feat: use MCP sampling to classify grounding strategy#173
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mattpodwysocki wants to merge 1 commit intofeat/ground-location-toolfrom
Open
feat: use MCP sampling to classify grounding strategy#173mattpodwysocki wants to merge 1 commit intofeat/ground-location-toolfrom
mattpodwysocki wants to merge 1 commit intofeat/ground-location-toolfrom
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…ion_tool When the client supports sampling, ground_location_tool asks the LLM to classify the query intent into one of four strategies before making any Mapbox API calls: - neighborhood: reverse geocode at neighborhood/locality level + isochrone - routing: reverse geocode at address/poi level for precise routable coords - poi: category search with boosted limit (min 15), no isochrone - region: reverse geocode at region/district level + isochrone Falls back gracefully to 'neighborhood' if sampling is not supported, returns an unexpected classification, or throws an error — so existing clients are unaffected. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Summary
Enhances
ground_location_toolwith MCP sampling to intelligently classify what kind of location grounding a query needs before making any Mapbox API calls.Grounding strategies
neighborhoodroutingpoiregionHow it works
When the client supports
sampling, the tool sends a short classification prompt to the LLM asking it to pick one of the four strategies. The response shapes which Mapbox APIs are called and what parameters are used — e.g. routing getstypes=address,poifor precise routable coordinates, while poi boosts the result limit to at least 15.Graceful degradation: Falls back to
neighborhood(current behavior) if:samplingcapabilityNo changes to the tool's public interface, schema, or registry wiring.
Test plan
npm testpassesnpm run buildsucceeds🤖 Generated with Claude Code