en un clic
mapbox-location-grounding
// Compose Mapbox MCP tools to produce grounded, cited location-aware responses from live data instead of training data
// Compose Mapbox MCP tools to produce grounded, cited location-aware responses from live data instead of training data
| name | mapbox-location-grounding |
| description | Compose Mapbox MCP tools to produce grounded, cited location-aware responses from live data instead of training data |
Teaches AI assistants how to ground location-aware responses in live Mapbox data by composing MCP tools into a structured, cited answer. Use this instead of relying on training data for place names, POIs, ratings, or travel times — which are stale and prone to hallucination.
Ground responses when the user asks about:
Never answer location questions from training data alone. Always retrieve live data.
If ground_location_tool is available, use it — it handles reverse geocoding, POI search, place details enrichment, isochrone, and a static map image in one call:
ground_location_tool(
longitude, latitude,
query: "restaurant", // optional — category or subcategory of nearby places to find
profile: "mapbox/walking", // optional — travel profile for isochrone
contours_minutes: [5, 10, 15]
)
Returns:
Do not call reverse_geocode_tool, category_search_tool, place_details_tool, or isochrone_tool separately — they are already composed inside this tool.
The query parameter accepts category or subcategory terms — not attribute preferences:
"restaurant", "coffee", "park", "Italian restaurant", "EV charging station""family-friendly", "fast charging", "outdoor seating" — these are not filterable attributes in Mapbox dataTo help users find places matching a preference (e.g. "family-friendly"), search by category ("restaurant") and use the returned rating and price data to inform the recommendation.
If ground_location_tool is not available, build the grounded response by composing these tools in order:
reverse_geocode_tool(longitude, latitude, types: "neighborhood,locality,place")
Returns: neighborhood, city, region, country. This is the anchor for the response.
For specific names or brands:
search_and_geocode_tool(query, proximity: {longitude, latitude}, limit: 10)
For generic categories:
category_search_tool(category, proximity: {longitude, latitude}, limit: 10)
For each POI with a mapbox_id, call in parallel:
place_details_tool(mapbox_id, attribute_sets: ["visit"])
Returns: rating, price level, popularity, and opening hours per place.
isochrone_tool(
coordinates: {longitude, latitude},
profile: "mapbox/walking", // or "mapbox/driving", "mapbox/cycling", "mapbox/driving-traffic"
contours_minutes: [5, 10, 15]
)
Returns a polygon showing what's reachable within each time threshold.
static_map_image_tool(longitude, latitude, zoom: 14)
Returns a map image that can be included in the response for visual context.
Always structure grounded responses with explicit citations:
Place: [neighborhood, city from reverse_geocode]
Nearby [category]: [list from search/category tool, with names, ratings, prices, and distances]
Travel context: [X min walk / Y min drive from isochrone]
Sources: Mapbox Search, Mapbox Directions (live data)
Example grounded response:
SoMa, San Francisco, CA (live Mapbox data)
Restaurants within walking distance:
- Bix Restaurant $$ ★8.4 — 56 Gold St (180m)
- The Bird $ ★7.9 — 115 New Montgomery St (320m)
- Oren's Hummus $$ ★8.1 — 131 Townsend St (510m)
Reachable by walking: 5 min, 10 min, 15 min
Sources: Mapbox Geocoding API, Mapbox Search API, Mapbox Place Details API, Mapbox Isochrone API, Mapbox Static Images API
For questions about travel between two locations, use directions_tool. For questions about reachable area, use isochrone_tool. For comparing travel times across multiple locations, use matrix_tool.
"How long does it take to drive from Pike Place Market to Capitol Hill?" "What's the fastest route from the hotel to the airport?"
directions_tool(
waypoints: [{longitude, latitude}, {longitude, latitude}],
profile: "mapbox/driving-traffic" // live traffic; or "mapbox/walking", "mapbox/cycling", "mapbox/driving"
)
Returns: duration (with live traffic), distance, turn-by-turn steps, and an encoded polyline for map rendering. Supports up to 25 waypoints for multi-stop routes.
"What's reachable within a 10-minute walk?" "Show me what I can reach in 15 minutes by car from here"
isochrone_tool(
coordinates: {longitude, latitude},
profile: "mapbox/walking",
contours_minutes: [5, 10, 15]
)
Returns a polygon showing the area reachable within each time threshold. Combine with category_search_tool or ground_location_tool to answer "what restaurants are within a 10-minute walk?" — use the isochrone to define the boundary, then search within it.
"Which of these three offices is closest to my location?" "What are travel times from this warehouse to each of our delivery zones?" "Compare commute times to multiple locations"
Use matrix_tool — do NOT call directions_tool separately for each pair. Matrix batches all pairs in a single API call.
matrix_tool(
sources: [{longitude, latitude}, ...],
destinations: [{longitude, latitude}, ...],
profile: "mapbox/driving-traffic"
)
Returns a matrix of durations and distances between every source/destination pair. Rank results by duration to find the nearest location. One matrix_tool call replaces N separate directions_tool calls.
For "find [category] within X minutes of [location]":
search_and_geocode_tool(address)isochrone_tool(coordinates, profile, contours_minutes)ground_location_tool(longitude, latitude, query: "category") — the isochrone
contours tell the user what's within each time bandOr more directly: ground_location_tool returns both nearby POIs and isochrone reachability in one
call, which covers most proximity + routing use cases without additional composition.
Pike Place Market → Capitol Hill, Seattle
By car (with traffic): 12 min, 3.2 km via Pine St By walking: 28 min, 2.1 km By cycling: 14 min, 2.3 km
Source: Mapbox Directions API (live traffic)
| Training Data | Mapbox Grounding | |
|---|---|---|
| POI accuracy | Stale, hallucinated | Live, verified |
| Ratings/price | Often wrong | Live via Place Details |
| Business hours | Often wrong | Live via Place Details |
| Travel times | Estimated | Live traffic via Directions |
| Reachable area | Not available | Isochrone polygons |
| Multi-stop routing | Not available | Up to 25 waypoints |
| New places | Missing | Indexed |
| Map image | None | Inline static map |
| Citations | None | Tool + API source |
search_and_geocode_tool before running category search.directions_tool or isochrone_toolreverse_geocode_tool + category_search_tool + place_details_tool separately when ground_location_tool is availableOfficial integration patterns for Mapbox Maps SDK on iOS. Covers installation, adding markers, user location, custom data, styles, camera control, and featureset interactions. Based on official Mapbox documentation.
Official integration patterns for the Mapbox Maps Flutter SDK. Covers installation, iOS/Android platform setup, access token configuration, MapWidget initialization, camera control, annotations with tap handling, user location, and loading GeoJSON. Based on official Mapbox documentation.
Official integration patterns for Mapbox Maps SDK on Android. Covers installation, adding markers, user location, custom data, styles, camera control, and featureset interactions. Based on official Mapbox documentation.
Expert guidance on choosing the right Mapbox search tool and parameters for geocoding, POI search, and location discovery
Integration patterns for Mapbox MCP Server in AI applications and agent frameworks. Covers runtime integration with pydantic-ai, mastra, LangChain, and custom agents. Use when building AI-powered applications that need geospatial capabilities.
Common patterns for building store locators, restaurant finders, and location-based search applications with Mapbox. Covers marker display, filtering, distance calculation, and interactive lists.