# mapbox-mcp-runtime-patterns

Guides agents on integrating Mapbox MCP Server into AI frameworks. Helps models choose between local Turf.js math and live Mapbox routing APIs.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 1400 installs · ★ 83
- Author: mapbox
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/mapbox/mapbox-agent-skills/tree/HEAD/skills/mapbox-mcp-runtime-patterns/SKILL.md
- Updated: 2026-10-23
- HTML: https://affpapa.org/en/nevibecode/skills/mapbox-mcp-runtime-patterns

## What it does

The skill supplies production patterns for running Mapbox MCP Server inside frameworks like Pydantic AI, Mastra, and LangChain. It teaches the agent when to execute free offline geometry tools using Turf.js and when to call external Mapbox APIs.

Reference files organize guidance for caching, batching, error handling, and domain architectures like real estate or food delivery. The agent learns to pick straight-line calculations for basic proximity, saving road routing and isochrones for live transit questions.

Live tools require a valid `MAPBOX_ACCESS_TOKEN`, so unauthenticated agents are limited to local Turf.js calculations.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add mapbox/mapbox-agent-skills --skill mapbox-mcp-runtime-patterns -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/mapbox-mcp-runtime-patterns/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/mapbox-mcp-runtime-patterns/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add mapbox/mapbox-agent-skills --skill mapbox-mcp-runtime-patterns -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/mapbox-mcp-runtime-patterns/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add mapbox/mapbox-agent-skills --skill mapbox-mcp-runtime-patterns -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/mapbox-mcp-runtime-patterns/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install mapbox/mapbox-agent-skills mapbox-mcp-runtime-patterns
```

2. **Manually: put the files in place**
- File: `.github/skills/mapbox-mcp-runtime-patterns/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add mapbox/mapbox-agent-skills --skill mapbox-mcp-runtime-patterns -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/mapbox/mapbox-agent-skills --path skills/mapbox-mcp-runtime-patterns
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/mapbox-mcp-runtime-patterns/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add mapbox/mapbox-agent-skills --skill mapbox-mcp-runtime-patterns -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/mapbox/mapbox-agent-skills/tree/HEAD/skills/mapbox-mcp-runtime-patterns/SKILL.md

## When to use it
- connect Mapbox MCP Server to Pydantic AI or LangChain agents
- separate offline Turf.js calculations from billed API calls
- calculate reachability polygons using isochrones
- implement caching and error handling for geospatial workflows

## Example prompts
- Show me an integration pattern for Mapbox MCP Server in Pydantic AI
- Which tool should the agent use to test if a point is inside a polygon?
- Configure directions_tool and matrix_tool for route estimation in Mastra

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 0c1925550bd562d5.

BEGIN THIRD-PARTY FILE 0c1925550bd562d5
```text
---
name: mapbox-mcp-runtime-patterns
description: 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.
---

# Mapbox MCP Runtime Patterns

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](https://github.com/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
```
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