Mapbox Geospatial Operations Skill

Expert guidance for AI assistants on choosing the right geospatial tools from the Mapbox MCP Server. Focuses on selecting tools based on what the problem requires - geometric calculations vs routing, straight-line vs road network, and accuracy needs.

Core Principle: Problem Type Determines Tool Choice

The Mapbox MCP Server provides two categories of geospatial tools:

1. Offline Geometric Tools - Use Turf.js for pure geometric/spatial calculations
2. Routing & Navigation APIs - Use Mapbox APIs when you need real-world routing, traffic, or travel times

The key question: What does the problem actually require?

Decision Framework

Decision Matrices by Use Case

Distance Calculations

User asks: "How far is X from Y?"

Example: "What's the distance between these 5 warehouses?"

• As the crow flies → distance_tool (10 calculations, instant)
• As the crow drives → matrix_tool (5×5 matrix, one API call, returns actual route distances)

Key insight: Use the tool that matches what "distance" means in context. Always clarify: crow flies or crow drives?

Proximity and Containment

User asks: "Which points are near/inside this area?"

Example: "Are these 200 addresses in our 30-minute delivery zone?"

1. Create zone → isochrone_tool (routing API - need travel time)
2. Check addresses → point_in_polygon_tool (geometric - 200 instant checks)

Key insight: Routing for creating travel-time zones, geometric for containment checks

Routing and Navigation

User asks: "What's the best route?"

Example: "Navigate from hotel to airport"

• Need turn-by-turn → directions_tool
• Just need to know "it's northeast" → bearing_tool

Key insight: Routing tools for actual navigation, geometric tools for directional info

Area and Shape Operations

User asks: "Create a zone around this location"

Example: "Show 5km coverage around each store"

• 5km radius → buffer_tool (geometric circles)
• "What customers can reach in 15 min?" → isochrone_tool (routing-based)

Key insight: Geometric tools for distance-based zones, routing tools for time-based zones

Performance and Scale Considerations

When Volume Affects Tool Choice

Small operations (< 100 calculations):

• Geometric tools: Instant, iterate freely
• Routing APIs: Fast enough for most uses

Medium operations (100-1,000 calculations):

• Geometric tools: Still fast, no concerns
• Routing APIs: Consider batch operations (matrix_tool)

Large operations (> 1,000 calculations):

• Geometric tools: May need optimization but still fast
• Routing APIs: Definitely use batch tools (matrix_tool handles up to 25×25)

Key insight: Volume rarely affects geometric tool choice, but routing APIs have batch tools for efficiency

Real-Time vs Batch

Architecture note for high-frequency geofencing: If the application calls containment checks at very high rates (e.g., 50 vehicles every 2 seconds = 25 checks/second), calling MCP tools over the network adds agent-reasoning overhead that makes it impractical. In those cases, recommend using Turf.js directly in-process (turf.booleanPointInPolygon) for the hot path, and reserve MCP tools for peripheral tasks like zone definition (isochrone_tool), rerouting (directions_tool), or visualization (static_map_image_tool).

Common Scenarios and Optimal Approaches

Scenario 1: Store Locator

User: "Find the closest store and show 5km coverage"

Optimal approach:

1. Search stores → category_search_tool (returns distances automatically)
2. Create coverage zone → buffer_tool (5km geometric circle)
3. Visualize → static_map_image_tool

Why: Search already gives distances; geometric buffer for simple radius

Scenario 2: Delivery Route Optimization

User: "Optimize delivery to 8 addresses / stops"

Optimal approach:

1. Geocode addresses (if needed) → Use search_and_geocode_tool to convert any street addresses to coordinates. Even when coordinates are already provided, mention this as an optional pre-step — real-world delivery lists often contain a mix of addresses and coordinates.
2. Optimize route → optimization_tool (TSP solver — reorders stops to minimize total drive time)

Why optimization_tool and NOT these alternatives:

• directions_tool only routes A → B (or through fixed-order waypoints). It does NOT reorder stops — if you pass 8 stops, it routes them in the order given, which is almost never optimal.
• matrix_tool gives travel times between all pairs of stops (8×8 = 64 values), but it does NOT compute the optimal ordering. You'd need to solve TSP yourself on top of the matrix — optimization_tool does this for you in one call.

Always mention search_and_geocode_tool as a useful companion for geocoding delivery addresses before optimization.

Scenario 3: Service Area Validation

User: "Which of these 200 addresses can we deliver to in 30 minutes?"

Optimal approach:

1. Create delivery zone → isochrone_tool (30-minute driving)
2. Check each address → point_in_polygon_tool (200 geometric checks)

Why: Routing for accurate travel-time zone, geometric for fast containment checks

Scenario 4: GPS Trace Analysis

User: "How long was this bike ride?"

Optimal approach:

1. Clean GPS trace → map_matching_tool (snap to bike paths)
2. Get distance → Use API response or calculate with distance_tool

Why: Need road/path matching; distance calculation either way works

Scenario 5: Coverage Analysis

User: "What's our total service area?"

Optimal approach:

1. Create buffers around each location → buffer_tool
2. Calculate total area → area_tool
3. Or, if time-based → isochrone_tool for each location

Why: Geometric for distance-based coverage, routing for time-based

Anti-Patterns: Using the Wrong Tool Type

❌ Don't: Use geometric tools for routing questions

// WRONG: User asks "how long to drive there?"
distance_tool({ from: A, to: B });
// Returns 10km as the crow flies, but actual drive is 15km

// CORRECT: Need routing for driving distance
directions_tool({
  coordinates: [
    { longitude: A[0], latitude: A[1] },
    { longitude: B[0], latitude: B[1] }
  ],
  routing_profile: 'mapbox/driving'
});
// Returns actual road distance and drive time as the crow drives

Why wrong: As the crow flies ≠ as the crow drives

❌ Don't: Use routing APIs for geometric operations

// WRONG: Check if point is in polygon
// (Can't do this with routing APIs)

// CORRECT: Pure geometric operation
point_in_polygon_tool({ point: location, polygon: boundary });

Why wrong: Routing APIs don't do geometric containment

❌ Don't: Confuse "near" with "reachable"

// User asks: "What's reachable in 20 minutes?"

// WRONG: 20-minute distance at average speed
distance_tool + calculate 20min * avg_speed

// CORRECT: Actual routing with road network
isochrone_tool({
  coordinates: {longitude: startLng, latitude: startLat},
  contours_minutes: [20],
  profile: "mapbox/driving"
})

Why wrong: Roads aren't straight lines; traffic varies

❌ Don't: Use routing when bearing is sufficient

// User asks: "Which direction is the airport?"

// OVERCOMPLICATED: Full routing
directions_tool({
  coordinates: [
    { longitude: hotel[0], latitude: hotel[1] },
    { longitude: airport[0], latitude: airport[1] }
  ]
});

// BETTER: Just need bearing
bearing_tool({ from: hotel, to: airport });
// Returns: "Northeast (45°)"

Why better: Simpler, instant, answers the actual question

Hybrid Approaches: Combining Tool Types

Some problems benefit from using both geometric and routing tools:

Pattern 1: Routing + Geometric Filter

1. directions_tool → Get route geometry
2. buffer_tool → Create corridor around route
3. category_search_tool → Find POIs in corridor
4. point_in_polygon_tool → Filter to those actually along route

Use case: "Find gas stations along my route"

Pattern 2: Routing + Distance Calculation

1. category_search_tool → Find 10 nearby locations
2. distance_tool → Calculate straight-line distances (geometric)
3. For top 3, use directions_tool → Get actual driving time

Use case: Quickly narrow down, then get precise routing for finalists

Pattern 3: Isochrone + Containment

1. isochrone_tool → Create travel-time zone (routing)
2. point_in_polygon_tool → Check hundreds of addresses (geometric)

Use case: "Which customers are in our delivery zone?"

Decision Algorithm

When user asks a geospatial question:

1. Does it require routing, roads, or travel times?
   YES → Use routing API (directions, matrix, isochrone, optimization)
   NO → Continue

2. Does it require traffic awareness?
   YES → Use directions_tool or isochrone_tool with traffic profile
   NO → Continue

3. Is it a geometric/spatial operation?
   - Distance between points (straight-line) → distance_tool
   - Point containment → point_in_polygon_tool
   - Area calculation → area_tool
   - Buffer/zone → buffer_tool
   - Direction/bearing → bearing_tool
   - Geometric center → centroid_tool
   - Bounding box → bounding_box_tool
   - Simplification → simplify_tool

4. Is it a search/discovery operation?
   YES → Use search tools (search_and_geocode, category_search)

Key Decision Questions

Before choosing a tool, ask:

1. Does "distance" mean as the crow flies or as the crow drives?

   • As the crow flies (straight-line) → geometric tools
   • As the crow drives (road distance) → routing APIs

2. Does the user need travel time?

   • Yes → routing APIs (only they know speeds/traffic)
   • No → geometric tools may suffice

3. Is this about roads/paths or pure spatial relationships?

   • Roads/paths → routing APIs
   • Spatial relationships → geometric tools

4. Does this need to happen in real-time with low latency?

   • Yes + geometric problem → offline tools (instant)
   • Yes + routing problem → use routing APIs (still fast)

5. Is accuracy critical, or is approximation OK?

   • Critical + routing → routing APIs
   • Approximation OK → geometric tools may work

Terminology Guide

Understanding what users mean:

Quick Reference

Geometric Operations (Offline Tools)

• distance_tool - Straight-line distance between two points
• bearing_tool - Compass direction from A to B
• midpoint_tool - Midpoint between two points
• point_in_polygon_tool - Is point inside polygon?
• area_tool - Calculate polygon area
• buffer_tool - Create circular buffer/zone
• centroid_tool - Geometric center of polygon
• bbox_tool - Min/max coordinates of geometry
• simplify_tool - Reduce geometry complexity

Routing & Navigation (APIs)

• directions_tool - Turn-by-turn routing
• matrix_tool - Many-to-many travel times
• optimization_tool - Route optimization (TSP)
• isochrone_tool - Travel-time zones
• map_matching_tool - Snap GPS to roads

When to Use Each Category

Use Geometric Tools When:

• Problem is spatial/mathematical (containment, area, bearing)
• Straight-line distance is appropriate
• Need instant results for real-time checks
• Pure geometry (no roads/traffic involved)

Use Routing APIs When:

• Need actual driving/walking/cycling distances
• Need travel times
• Need to consider road networks
• Need traffic awareness
• Need route optimization
• Need turn-by-turn directions

REST API honesty (Directions / Isochrone)

When generating browser demos against Mapbox REST APIs (not only MCP tools):

Directions — use the route object metrics

const route = data.routes[0];
// GOOD — meters / seconds from the API
stats.textContent =
  `Distance ${(route.distance / 1000).toFixed(2)} km · ` + `Duration ${Math.round(route.duration / 60)} min`;

// BAD — cosmetic labels or hardcoded ETAs that look like a working demo
// "Len 0.00 km · Time 2 min" / Math.round(120/60)

Isochrone — request multiple contours when the prompt asks for bands

// GOOD — three travel-time bands
`contours_minutes=15,30,60`;

// BAD — a single contour when the UX needs 15 / 30 / 60
`contours_minutes=30`;

Integration with Other Skills

Works with:

• mapbox-search-patterns: Search for locations, then use geospatial operations
• mapbox-web-performance-patterns: Optimize rendering of geometric calculations
• mapbox-token-security: Ensure requests use properly scoped tokens

Resources

• Mapbox MCP Server
• Turf.js Documentation (Powers geometric tools)
• Mapbox Directions API
• Mapbox Isochrone API
• Mapbox Matrix API
• Mapbox Optimization API