Mapbox Geospatial Operations
This is essentially a decision tree for when to use geometric calculations versus Mapbox's routing APIs. The core insight is simple but easy to mess up: use Turf.js for "as the crow flies" problems (straight-line distance, point-in-polygon checks, buffers) and routing APIs for "as the crow drives" problems (actual road distance, travel time, traffic). The matrices are thorough, covering distance calculations, proximity checks, and performance tradeoffs at different scales. Most useful when you're building something that mixes both types of operations, like creating a 30-minute delivery zone with isochrones and then doing fast geometric checks on whether addresses fall inside it.
- skills.sh installs
- 2.3K
- GitHub stars
- 86
- last updated
- Aug 21, 2026
Install
$ npx -y skills add mapbox/mapbox-agent-skills --skill mapbox-geospatial-operations --agent claude-codeInstalls into .claude/skills of the current project.
Files
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:
- Offline Geometric Tools - Use Turf.js for pure geometric/spatial calculations
- 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
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- Repository
- github.com/mapbox/mapbox-agent-skills
- Categories
- AI & Agent Building, Debugging
- First seen
- Apr 16, 2026
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