MCPInstall

mapbox-location-grounding

by mapbox OfficialAI & Agents

Compose Mapbox MCP tools to produce grounded, cited location-aware responses from live data instead of training data

Installs
1.3K
Last 24h
—
Trending rank
—
Security
Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/mapbox/mapbox-agent-skills --skill mapbox-location-grounding
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads mapbox-location-grounding automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Mapbox Location Grounding Skill

Teaches AI assistants how to ground location-aware responses in live Mapbox data by composing MCP tools into a structured, cited answer. Use this instead of relying on training data for place names, POIs, ratings, or travel times — which are stale and prone to hallucination.

When to Use Grounding

Ground responses when the user asks about:

  • "What's near [location]?" or "What's around [coordinate]?"
  • "Describe this neighborhood / area"
  • "Find [category] within walking/driving distance"
  • "What can I do near [address]?"
  • "How long does it take to get from A to B?"
  • "What's within a 10-minute walk of here?"
  • "How far is it between these locations?"
  • Real estate, travel, mobility, or local discovery use cases
  • Any question where place accuracy, recency, or travel time matters

Never answer location questions from training data alone. Always retrieve live data.

Grounding Tool Composition

Preferred: single tool call

If ground_location_tool is available, use it — it handles reverse geocoding, POI search, place details enrichment, isochrone, and a static map image in one call:

ground_location_tool(
  longitude, latitude,
  query: "restaurant",   // optional — category or subcategory of nearby places to find
  profile: "mapbox/walking",    // optional — travel profile for isochrone
  contours_minutes: [5, 10, 15]
)

Returns:

  • Neighborhood/place name from reverse geocoding
  • Nearby POIs with distances, ratings, price levels, and popularity (when available)
  • Travel-time reachability from isochrone
  • A static map image for visual context
  • Citations for all data sources

Do not call reverse_geocode_tool, category_search_tool, place_details_tool, or isochrone_tool separately — they are already composed inside this tool.

Query parameter

The query parameter accepts category or subcategory terms — not attribute preferences:

  • Supported: "restaurant", "coffee", "park", "Italian restaurant", "EV charging station"
  • Not supported: "family-friendly", "fast charging", "outdoor seating" — these are not filterable attributes in Mapbox data

To help users find places matching a preference (e.g. "family-friendly"), search by category ("restaurant") and use the returned rating and price data to inform the recommendation.

Fallback: manual composition

If ground_location_tool is not available, build the grounded response by composing these tools in order:

Step 1 — Establish place context

reverse_geocode_tool(longitude, latitude, types: "neighborhood,locality,place")

Returns: neighborhood, city, region, country. This is the anchor for the response.

Step 2 — Retrieve nearby POIs

For specific names or brands:

search_and_geocode_tool(query, proximity: {longitude, latitude}, limit: 10)

For generic categories:

category_search_tool(category, proximity: {longitude, latitude}, limit: 10)

Step 3 — Enrich POIs with ratings and price (optional but high-value)

For each POI with a mapbox_id, call in parallel:

place_details_tool(mapbox_id, attribute_sets: ["visit"])

Returns: rating, price level, popularity, and opening hours per place.

Step 4 — Add travel-time context (optional but high-value)

isochrone_tool(
  coordinates: {longitude, latitude},
  profile: "mapbox/walking",    // or "mapbox/driving", "mapbox/cycling", "mapbox/driving-traffic"
  contours_minutes: [5, 10, 15]
)

Returns a polygon showing what's reachable within each time threshold.

Step 5 — Visual grounding (optional)

static_map_image_tool(longitude, latitude, zoom: 14)

Returns a map image that can be included in the response for visual context.

Grounded Response Structure

Always structure grounded responses with explicit citations:

Place: [neighborhood, city from reverse_geocode]
Nearby [category]: [list from search/category tool, with names, ratings, prices, and distances]
Travel context: [X min walk / Y min drive from isochrone]
Sources: Mapbox Search, Mapbox Directions (live data)

Example grounded response:

SoMa, San Francisco, CA (live Mapbox data)

Restaurants within walking distance:

  • Bix Restaurant $$ ★8.4 — 56 Gold St (180m)
  • The Bird $ ★7.9 — 115 New Montgomery St (320m)
  • Oren's Hummus $$ ★8.1 — 131 Townsend St (510m)

Reachable by walking: 5 min, 10 min, 15 min

Sources: Mapbox Geocoding API, Mapbox Search API, Mapbox Place Details API, Mapbox Isochrone API, Mapbox Static Images API

Routing Grounding

For questions about travel between two locations, use directions_tool. For questions about reachable area, use isochrone_tool. For comparing travel times across multiple locations, use matrix_tool.

Point-to-point travel time and distance

"How long does it take to drive from Pike Place Market to Capitol Hill?" "What's the fastest route from the hotel to the airport?"

directions_tool(
  waypoints: [{longitude, latitude}, {longitude, latitude}],
  profile: "mapbox/driving-traffic"   // live traffic; or "mapbox/walking", "mapbox/cycling", "mapbox/driving"
)

Returns: duration (with live traffic), distance, turn-by-turn steps, and an encoded polyline for map rendering. Supports up to 25 waypoints for multi-stop routes.

Area reachability ("within X minutes")

"What's reachable within a 10-minute walk?" "Show me what I can reach in 15 minutes by car from here"

isochrone_tool(
  coordinates: {longitude, latitude},
  profile: "mapbox/walking",
  contours_minutes: [5, 10, 15]
)

Returns a polygon showing the area reachable within each time threshold. Combine with category_search_tool or ground_location_tool to answer "what restaurants are within a 10-minute walk?" — use the isochrone to define the boundary, then search within it.

Multi-location travel time matrix

"Which of these three offices is closest to my location?" "What are travel times from this warehouse to each of our delivery zones?" "Compare commute times to multiple locations"

Use matrix_tool — do NOT call directions_tool separately for each pair. Matrix batches all pairs in a single API call.

matrix_tool(
  sources: [{longitude, latitude}, ...],
  destinations: [{longitude, latitude}, ...],
  profile: "mapbox/driving-traffic"
)

Returns a matrix of durations and distances between every source/destination pair. Rank results by duration to find the nearest location. One matrix_tool call replaces N separate directions_tool calls.

Proximity search with routing context

For "find [category] within X minutes of [location]":

  1. Geocode the origin if needed: search_and_geocode_tool(address)
  2. Get the reachable area: isochrone_tool(coordinates, profile, contours_minutes)
  3. Search for POIs: ground_location_tool(longitude, latitude, query: "category") — the isochrone contours tell the user what's within each time band

Or more directly: ground_location_tool returns both nearby POIs and isochrone reachability in one call, which covers most proximity + routing use cases without additional composition.

Example routing response

Pike Place Market → Capitol Hill, Seattle

By car (with traffic): 12 min, 3.2 km via Pine St By walking: 28 min, 2.1 km By cycling: 14 min, 2.3 km

Source: Mapbox Directions API (live traffic)

What Mapbox Grounding Offers vs. Training Data

Training DataMapbox Grounding
POI accuracyStale, hallucinatedLive, verified
Ratings/priceOften wrongLive via Place Details
Business hoursOften wrongLive via Place Details
Travel timesEstimatedLive traffic via Directions
Reachable areaNot availableIsochrone polygons
Multi-stop routingNot availableUp to 25 waypoints
New placesMissingIndexed
Map imageNoneInline static map
CitationsNoneTool + API source

Important Limitations

  • Attribute filtering (family-friendly, outdoor seating, fast charging) is not supported by the category search API. Use category terms and let rating/price data inform preference-based recommendations.
  • POI coverage varies by region. If search returns few results, say so rather than padding with guesses.
  • Coordinates required for proximity search — if the user provides an address, geocode it first with search_and_geocode_tool before running category search.

Anti-Patterns to Avoid

  • Answering "what's near X?" from training data without calling search tools
  • Estimating travel times without calling directions_tool or isochrone_tool
  • Hallucinating business names, hours, or ratings
  • Calling reverse_geocode_tool + category_search_tool + place_details_tool separately when ground_location_tool is available
  • Using attribute terms like "family-friendly" as the query parameter — use the category instead
  • Returning raw tool output without synthesizing into a readable response
  • Omitting citations — always indicate the response is grounded in live Mapbox data

FAQ

What does the mapbox-location-grounding skill do?

Compose Mapbox MCP tools to produce grounded, cited location-aware responses from live data instead of training data

How do I install mapbox-location-grounding?

Run npx skills add https://github.com/mapbox/mapbox-agent-skills --skill mapbox-location-grounding in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/mapbox-location-grounding/ (personal) or .claude/skills/mapbox-location-grounding/ (project).

Which AI agents can use mapbox-location-grounding?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is mapbox-location-grounding safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains mapbox-location-grounding?

It is published by mapbox in mapbox/mapbox-agent-skills, and it is an official skill from the maker of the technology it covers. It has 1,273 recorded installs.

More from mapbox/mapbox-agent-skills

View all →

mapbox-web-integration-patterns

mapbox/mapbox-agent-skills

Official integration patterns for Mapbox GL JS across popular web frameworks (React, Vue, Svelte, Angular). Covers setup, lifecycle management, token handling, search integration, and common pitfalls. Based on Mapbox's create-web-app scaffolding tool.

OfficialFrontend & Design2.6K installs

mapbox-web-performance-patterns

mapbox/mapbox-agent-skills

Performance optimization patterns for Mapbox GL JS web applications. Covers initialization waterfalls, bundle size, rendering performance, memory management, and web optimization. Prioritized by impact on user experience.

OfficialCode Quality & Workflow2.5K installs

mapbox-style-patterns

mapbox/mapbox-agent-skills

Common style patterns, layer configurations, and recipes for typical mapping scenarios including restaurant finders, real estate, data visualization, navigation, delivery/logistics, and more. Use when implementing specific map use cases or looking for proven style patterns.

OfficialAI & Agents2.4K installs

mapbox-geospatial-operations

mapbox/mapbox-agent-skills

Expert guidance on choosing the right geospatial tool based on problem type, accuracy requirements, and performance needs

OfficialAI & Agents2.2K installs

mapbox-data-visualization-patterns

mapbox/mapbox-agent-skills

Patterns for visualizing data on maps including choropleth maps, heat maps, 3D visualizations, data-driven styling, and animated data. Covers layer types, color scales, and performance optimization.

OfficialFrontend & Design2.1K installs

mapbox-cartography

mapbox/mapbox-agent-skills

Expert guidance on map design principles, color theory, visual hierarchy, typography, and cartographic best practices for creating effective and beautiful maps with Mapbox. Use when designing map styles, choosing colors, or making cartographic decisions.

OfficialFrontend & Design2.1K installs

Popular ai & agents skills

View category →

google-agents-cli-publish

google/agents-cli

This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini", "publish to Gemini" (formerly Gemini Enterprise), or needs guidance on the agents-cli publish gemini command. Also use when the user wants to "manage agents in Agent Registry", "list/update/delete registered agents", or "register an MCP server". Covers ADK vs A2A registration modes, programmatic and interactive usage, flag reference, auto-detection from deployment metadata, Agent Registry fleet management, and troubleshooting. Part of the agents-cli skills suite. Do NOT use for deployment (use google-agents-cli-deploy).

AI & Agents513.9K installs

google-agents-cli-eval

google/agents-cli

This skill should be used when the user wants to "run an evaluation", "evaluate my agent", "evaluate my ADK agent", "write an eval dataset", "analyze eval failures", "compare eval results", "optimize agent", or needs guidance on the Gemini platform eval methodology and the Quality Flywheel. Covers eval metrics, dataset schema, LLM-as-judge scoring, and common failure causes. Applies to any agents-cli project, whatever framework the agent is written in. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).

AI & Agents513.5K installs

skill-creator

anthropics/skills

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

OfficialAI & Agents416.4K installs

codex-pet

prime-skills/runcomfy-agent-skills

Codex Pet generator on RunComfy. Build a Codex-compatible Codex Pet spritesheet.webp + pet.json from a single reference image, drop it into ${CODEXHOME:-$HOME/.codex}/pets/ / and Codex picks it up as a custom Codex Pet next to the 8 built-ins. This skill produces the exact Codex Pet atlas Codex expects (1536x1872 PNG/WebP, 8 cols x 9 rows, 192x208 cells, 9 animation states — idle, running-right, running-left, waving, jumping, failed, waiting, running, review). Calls OpenAI GPT Image 2 edit ONCE via the local RunComfy CLI as runcomfy run openai/gpt-image-2/edit to produce a canonical Codex Pet pose, then assembles all 9 animation rows programmatically with ImageMagick micro-transforms — no Codex Pro, no $imagegen, no OPENAIAPIKEY required, only RUNCOMFYTOKEN. Triggers on "codex pet", "create codex pet", "make codex pet", "hatch codex pet", "/hatch image", "desktop pet codex", "codex pets", "spritesheet.webp", or any explicit ask to build a custom pet for OpenAI Codex.

AI & Agents402.1K installs

full-output-enforcement

leonxlnx/taste-skill

Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.

AI & Agents401K installs

executing-plans

obra/superpowers

Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available

AI & Agents245.7K installs