Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/mapbox/mapbox-agent-skills/mapbox-mcp-runtime-patternsnpx skills add mapbox/mapbox-agent-skills --skill mapbox-mcp-runtime-patternsgit clone --depth 1 https://github.com/mapbox/mapbox-agent-skillsWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00053 | $0.01375 |
| Opus 5 | $0.00026 | $0.00687 |
| Sonnet 5 | $0.00011 | $0.00275 |
| Haiku 4.5 | $0.00005 | $0.00137 |
Grade A, and why
mapbox-mcp-runtime-patterns scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 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
What ships with it
20 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- AGENTS.md 13 KB
- evals/evals.json 3.9 KB
- examples/python/crewai_example.py 9.1 KB runs code
- examples/python/pydantic_ai_example.py 5.6 KB runs code
- examples/python/requirements.txt 220 B
- examples/python/smolagents_example.py 9.2 KB runs code
- examples/README.md 7.2 KB
- examples/typescript/langchain-example.ts 7.7 KB runs code
- examples/typescript/mastra-example.ts 7.9 KB runs code
- examples/typescript/package-lock.json 117 KB
- examples/typescript/package.json 654 B
- examples/typescript/tsconfig.json 393 B
- references/crewai.md 6.9 KB
- references/custom-agent.md 7.4 KB
- references/langchain.md 5.7 KB
- references/mastra.md 2.6 KB
- references/production.md 9.5 KB
- references/pydantic-ai.md 2.8 KB
- references/smolagents.md 6.0 KB
- references/use-cases.md 2.9 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 199 lines · 53 tokens per session scan A fd2eb2e33ebf
mapbox-mcp-runtime-patterns is a skill published in the GitHub repository mapbox/mapbox-agent-skills (74 stars, last pushed 7d ago), licensed MIT. It adds 53 tokens to every session and 1,375 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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