This skill provides patterns for integrating the Mapbox MCP Server into AI applications for production use with geospatial capabilities.
What is Mapbox MCP Server?
The Mapbox MCP Server is a Model Context Protocol (MCP) server that provides AI agents with geospatial tools:
Offline Tools (Turf.js):
- Distance, bearing, midpoint calculations
- Point-in-polygon tests
- Area, buffer, centroid operations
- Bounding box, geometry simplification
- No API calls, instant results
Mapbox API Tools:
- Directions and routing
- Reverse geocoding
- POI category search
- Isochrones (reachability)
- Travel time matrices
- Static map images
- GPS trace map matching
- Multi-stop route optimization
Utility Tools:
- Server version info
- POI category list
Key benefit: Give your AI application geospatial superpowers without manually integrating multiple APIs.
Understanding Tool Categories
Before integrating, understand the key distinctions between tools to help your LLM choose correctly:
Distance: "As the Crow Flies" vs "Along Roads"
Straight-line distance (offline, instant):
- Tools:
distance_tool,bearing_tool,midpoint_tool - Use for: Proximity checks, "how far away is X?", comparing distances
- Example: "Is this restaurant within 2 miles?" →
distance_tool
Route distance (API, traffic-aware):
- Tools:
directions_tool,matrix_tool - Use for: Navigation, drive time, "how long to drive?"
- Example: "How long to drive there?" →
directions_tool
Search: Type vs Specific Place
Category/type search:
- Tool:
category_search_tool - Use for: "Find coffee shops", "restaurants nearby", browsing by type
- Example: "What hotels are near me?" →
category_search_tool
Specific place/address:
- Tool:
search_and_geocode_tool,reverse_geocode_tool - Use for: Named places, street addresses, landmarks
- Example: "Find 123 Main Street" →
search_and_geocode_tool
Travel Time: Area vs Route
Reachable area (what's within reach):
- Tool:
isochrone_tool - Returns: GeoJSON polygon of everywhere reachable
- Example: "What can I reach in 15 minutes?" →
isochrone_tool
Specific route (how to get there):
- Tool:
directions_tool - Returns: Turn-by-turn directions to one destination
- Example: "How do I get to the airport?" →
directions_tool
Cost & Performance
Offline tools (free, instant):
- No API calls, no token usage
- Use whenever real-time data not needed
- Examples:
distance_tool,point_in_polygon_tool,area_tool
API tools (requires token, counts against usage):
- Real-time traffic, live POI data, current conditions
- Use when accuracy and freshness matter
- Examples:
directions_tool,category_search_tool,isochrone_tool
Best practice: Prefer offline tools when possible, use API tools when you need real-time data or routing.
Installation & Setup
Option 1: Hosted Server (Recommended)
Easiest integration - Use Mapbox's hosted MCP server at:
https://mcp.mapbox.com/mcp
No installation required. Simply pass your Mapbox access token in the Authorization header.
Benefits:
- No server management
- Always up-to-date
- Production-ready
- Lower latency (Mapbox infrastructure)
Authentication:
Use token-based authentication (standard for programmatic access):
Authorization: Bearer your_mapbox_token
Note: The hosted server also supports OAuth, but that's primarily for interactive flows (coding assistants, not production apps).
Option 2: Self-Hosted
For custom deployments or development:
npm install @mapbox/mcp-server
Or use directly via npx:
npx @mapbox/mcp-server
Environment setup:
export MAPBOX_ACCESS_TOKEN="your_token_here"
Reference Files
Detailed integration patterns and production guidance are organized into reference files. Load the ones relevant to your task.
-
Pydantic AI -- Type-safe Python agents Load:
references/pydantic-ai.md -
CrewAI -- Multi-agent orchestration Load:
references/crewai.md -
Smolagents -- Lightweight HuggingFace agents Load:
references/smolagents.md -
Mastra -- Multi-agent TypeScript systems Load:
references/mastra.md -
LangChain -- Conversational AI with tool chaining Load:
references/langchain.md -
Custom Agent -- Zillow/TripAdvisor/DoorDash-style patterns, architecture diagrams, hybrid approach Load:
references/custom-agent.md -
Use Cases -- Real Estate, Food Delivery, Travel Planning examples Load:
references/use-cases.md -
Production Patterns -- Caching, batch operations, tool descriptions, error handling, security, rate limiting, testing Load:
references/production.md
Resources
When to Use This Skill
Invoke this skill when:
- Integrating Mapbox MCP Server into AI applications
- Building AI agents with geospatial capabilities
- Architecting Zillow/TripAdvisor/DoorDash-style apps with AI
- Choosing between MCP, direct APIs, or SDKs
- Optimizing geospatial operations in production
- Implementing error handling for geospatial AI features
- Testing AI applications with geospatial tools