version: "1.0.1" name: mapbox-geospatial-operations description: Expert guidance on choosing the right geospatial tool based on problem type, accuracy requirements, and performance needs

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

1. Does the user need travel time?

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

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

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

1. 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)

1. 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

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