Mapbox Location Grounding

Mapbox Location Grounding Skill

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.

When to Use Grounding

Ground responses when the user asks about:

• "What's near [location]?" or "What's around [coordinate]?"
• "Describe this neighborhood / area"
• "Find [category] within walking/driving distance"
• "What can I do near [address]?"
• "How long does it take to get from A to B?"
• "What's within a 10-minute walk of here?"
• "How far is it between these locations?"
• Real estate, travel, mobility, or local discovery use cases
• Any question where place accuracy, recency, or travel time matters

Never answer location questions from training data alone. Always retrieve live data.

Grounding Tool Composition

Preferred: single tool call

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:

• Neighborhood/place name from reverse geocoding
• Nearby POIs with distances, ratings, price levels, and popularity (when available)
• Travel-time reachability from isochrone
• A static map image for visual context
• Citations for all data sources

Do not call reverse_geocode_tool, category_search_tool, place_details_tool, or isochrone_tool separately — they are already composed inside this tool.

Query parameter

The query parameter accepts category or subcategory terms — not attribute preferences:

• Supported: "restaurant", "coffee", "park", "Italian restaurant", "EV charging station"
• Not supported: "family-friendly", "fast charging", "outdoor seating" — these are not filterable attributes in Mapbox data

To 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.

Fallback: manual composition

If ground_location_tool is not available, build the grounded response by composing these tools in order:

Step 1 — Establish place context

reverse_geocode_tool(longitude, latitude, types: "neighborhood,locality,place")

Returns: neighborhood, city, region, country. This is the anchor for the response.

Step 2 — Retrieve nearby POIs

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)

Step 3 — Enrich POIs with ratings and price (optional but high-value)

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.

Step 4 — Add travel-time context (optional but high-value)

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.

Step 5 — Visual grounding (optional)

static_map_image_tool(longitude, latitude, zoom: 14)

Returns a map image that can be included in the response for visual context.

Grounded Response Structure

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_

Routing Grounding

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.

Point-to-point travel time and distance

"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.

Area reachability ("within X minutes")

"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.

Multi-location travel time matrix

"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.

Proximity search with routing context

For "find [category] within X minutes of [location]":

1. Geocode the origin if needed: search_and_geocode_tool(address) 2. Get the reachable area: isochrone_tool(coordinates, profile, contours_minutes) 3. Search for POIs: ground_location_tool(longitude, latitude, query: "category") — the isochrone contours tell the user what's within each time band

Or 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.

Example routing response

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)_

What Mapbox Grounding Offers vs. Training Data

Important Limitations

• Attribute filtering (family-friendly, outdoor seating, fast charging) is not supported by the category search API. Use category terms and let rating/price data inform preference-based recommendations.
• POI coverage varies by region. If search returns few results, say so rather than padding with guesses.
• Coordinates required for proximity search — if the user provides an address, geocode it first with search_and_geocode_tool before running category search.

Anti-Patterns to Avoid

• Answering "what's near X?" from training data without calling search tools
• Estimating travel times without calling directions_tool or isochrone_tool
• Hallucinating business names, hours, or ratings
• Calling reverse_geocode_tool + category_search_tool + place_details_tool separately when ground_location_tool is available
• Using attribute terms like "family-friendly" as the query parameter — use the category instead
• Returning raw tool output without synthesizing into a readable response
• Omitting citations — always indicate the response is grounded in live Mapbox data