Mapbox Store Locator Patterns logo

Mapbox Store Locator Patterns

Organization
mapbox
mapbox-store-locator-patterns

Common patterns for building store locators, restaurant finders, and location-based search applications with Mapbox. Covers marker display, filtering, distance calculation, and interactive lists.

Overview

Publishermapbox
Repositorymapbox-agent-skills
Skill namemapbox-store-locator-patterns
Stars
78
Forks
17
Bundled files
8
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 8 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by mapbox on GitHub. Read the source before you install it.

Installation

Install the Mapbox Store Locator Patterns AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mapbox/mapbox-agent-skills.git /tmp/mapbox-agent-skills
mkdir -p .claude/skills
cp -r /tmp/mapbox-agent-skills/skills/mapbox-store-locator-patterns .claude/skills/mapbox-store-locator-patterns
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mapbox Store Locator Patterns in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Mapbox Store Locator Patterns on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Mapbox Store Locator Patterns is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Store Locator Patterns Skill

Comprehensive patterns for building store locators, restaurant finders, and location-based search applications with Mapbox GL JS. Covers marker display, filtering, distance calculation, interactive lists, and directions integration.

When to Use This Skill

Use this skill when building applications that:

  • Display multiple locations on a map (stores, restaurants, offices, etc.)
  • Allow users to filter or search locations
  • Calculate distances from user location
  • Provide interactive lists synced with map markers
  • Show location details in popups or side panels
  • Integrate directions to selected locations

Dependencies

Required:

  • Mapbox GL JS v3.x
  • @turf/turf - For spatial calculations (distance, area, etc.)

Installation:

bash
npm install mapbox-gl @turf/turf

Core Architecture

Pattern Overview

A typical store locator consists of:

  1. Map Display - Shows all locations as markers
  2. Location Data - GeoJSON with store/location information
  3. Interactive List - Side panel listing all locations
  4. Filtering - Search, category filters, distance filters
  5. Detail View - Popup or panel with location details
  6. User Location - Geolocation for distance calculation. For the blue dot location indicator, use the built-in mapboxgl.GeolocateControl — simpler than custom markers.
  7. Directions - Route to selected location (optional)

Data Structure

GeoJSON format for locations:

json
{
  "type": "FeatureCollection",
  "features": [
    {
      "type": "Feature",
      "geometry": {
        "type": "Point",
        "coordinates": [-77.034084, 38.909671]
      },
      "properties": {
        "id": "store-001",
        "name": "Downtown Store",
        "address": "123 Main St, Washington, DC 20001",
        "phone": "(202) 555-0123",
        "hours": "Mon-Sat: 9am-9pm, Sun: 10am-6pm",
        "category": "retail",
        "website": "https://example.com/downtown"
      }
    }
  ]
}

Key properties:

  • id - Unique identifier for each location
  • name - Display name
  • address - Full address for display and geocoding
  • coordinates - [longitude, latitude] format
  • category - For filtering (retail, restaurant, office, etc.)
  • Custom properties as needed (hours, phone, website, etc.)

Basic Store Locator Implementation

Step 1: Initialize Map and Data

javascript
import mapboxgl from 'mapbox-gl';
import 'mapbox-gl/dist/mapbox-gl.css';

mapboxgl.accessToken = 'YOUR_MAPBOX_ACCESS_TOKEN';

// Store locations data
const stores = {
  type: 'FeatureCollection',
  features: [
    {
      type: 'Feature',
      geometry: {
        type: 'Point',
        coordinates: [-77.034084, 38.909671]
      },
      properties: {
        id: 'store-001',
        name: 'Downtown Store',
        address: '123 Main St, Washington, DC 20001',
        phone: '(202) 555-0123',
        category: 'retail'
      }
    }
    // ... more stores
  ]
};

const map = new mapboxgl.Map({
  container: 'map',
  style: 'mapbox://styles/mapbox/standard',
  center: [-77.034084, 38.909671],
  zoom: 11
});

Step 2: Add Markers to Map

Marker strategy by location count:

CountStrategyReason
Fewer than 100HTML MarkersFull DOM/CSS control; DOM node count is manageable
100–1,000Symbol Layer (default)Renders on the GPU via WebGL — one <canvas>, zero per-point DOM elements
More than 1,000ClusteringReduces visual clutter at large scale

HTML Markers create one DOM element per point. Beyond ~100 locations the browser spends too much time on layout/paint. Symbol layers bypass the DOM entirely — the GPU draws all points in a single WebGL draw call.

Symbol Layer implementation (best for 100–1,000 locations). For HTML Markers (fewer than 100) or Clustering (more than 1,000), see references/markers.md.

javascript
map.on('load', () => {
  // Add store data as source
  map.addSource('stores', {
    type: 'geojson',
    data: stores
  });

  // Add custom marker image
  map.loadImage('/marker-icon.png', (error, image) => {
    if (error) throw error;
    map.addImage('custom-marker', image);

    // Add symbol layer
    map.addLayer({
      id: 'stores-layer',
      type: 'symbol',
      source: 'stores',
      layout: {
        'icon-image': 'custom-marker',
        'icon-size': 0.8,
        'icon-allow-overlap': true,
        'text-field': ['get', 'name'],
        'text-font': ['Open Sans Bold', 'Arial Unicode MS Bold'],
        'text-offset': [0, 1.5],
        'text-anchor': 'top',
        'text-size': 12
      }
    });
  });

  // Handle marker clicks using Interactions API (recommended)
  map.addInteraction('store-click', {
    type: 'click',
    target: { layerId: 'stores-layer' },
    handler: (e) => {
      const store = e.feature;
      flyToStore(store);
      createPopup(store);
    }
  });

  // Or using traditional event listener:
  // map.on('click', 'stores-layer', (e) => {
  //   const store = e.features[0];
  //   flyToStore(store);
  //   createPopup(store);
  // });
  //
  // For why addInteraction is preferred over map.on(), and how to pair it with
  // setFeatureState/appearances for hover and selection styling, see the
  // "interactions" reference file in the mapbox-style-patterns skill.

  // Change cursor on hover
  map.on('mouseenter', 'stores-layer', () => {
    map.getCanvas().style.cursor = 'pointer';
  });

  map.on('mouseleave', 'stores-layer', () => {
    map.getCanvas().style.cursor = '';
  });
});

Step 3: Build Interactive Location List

javascript
function buildLocationList(stores) {
  const listingContainer = document.getElementById('listings');

  stores.features.forEach((store, index) => {
    const listing = listingContainer.appendChild(document.createElement('div'));
    listing.id = `listing-${store.properties.id}`;
    listing.className = 'listing';

    const link = listing.appendChild(document.createElement('a'));
    link.href = '#';
    link.className = 'title';
    link.id = `link-${store.properties.id}`;
    link.innerHTML = store.properties.name;

    const details = listing.appendChild(document.createElement('div'));
    details.innerHTML = `
      <p>${store.properties.address}</p>
      <p>${store.properties.phone || ''}</p>
    `;

    // Handle listing click
    link.addEventListener('click', (e) => {
      e.preventDefault();
      flyToStore(store);
      createPopup(store);
      highlightListing(store.properties.id);
    });
  });
}

function flyToStore(store) {
  map.flyTo({
    center: store.geometry.coordinates,
    zoom: 15,
    duration: 1000
  });
}

function createPopup(store) {
  const popups = document.getElementsByClassName('mapboxgl-popup');
  // Remove existing popups
  if (popups[0]) popups[0].remove();

  new mapboxgl.Popup({ closeOnClick: true })
    .setLngLat(store.geometry.coordinates)
    .setHTML(
      `<h3>${store.properties.name}</h3>
       <p>${store.properties.address}</p>
       <p>${store.properties.phone}</p>
       ${store.properties.website ? `<a href="${store.properties.website}" target="_blank">Visit Website</a>` : ''}`
    )
    .addTo(map);
}

// IMPORTANT: highlightListing MUST include scrollIntoView — without it,
// selecting a marker on the map won't scroll the sidebar to the listing.
function highlightListing(id) {
  // Remove existing highlights
  const activeItem = document.getElementsByClassName('active');
  if (activeItem[0]) {
    activeItem[0].classList.remove('active');
  }

  // Add highlight to selected listing
  const listing = document.getElementById(`listing-${id}`);
  listing.classList.add('active');

  // Scroll the selected listing into view (critical UX requirement)
  listing.scrollIntoView({ behavior: 'smooth', block: 'nearest' });
}

// Build the list on load
map.on('load', () => {
  buildLocationList(stores);
});

Reference Files

Load these references for additional patterns as needed:

ReferenceFileContents
HTML Markers & Clusteringreferences/markers.mdHTML Markers (< 100 locations), Clustering (> 1000 locations)
Search & Filterreferences/search-filter.mdText search, category filter
Geolocation & Directionsreferences/geolocation-directions.mdUser location, distance calculation, route directions
Styling & Layoutreferences/styling-layout.mdFull HTML/CSS layout, custom marker CSS
Performance & A11yreferences/optimization-a11y.mdDebounced search, data management, error handling, accessibility
Variations & Reactreferences/variations-react.mdMobile-first, fullscreen, map-only, React implementation

Resources

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Mapbox Store Locator Patterns AI skill do?

Common patterns for building store locators, restaurant finders, and location-based search applications with Mapbox. Covers marker display, filtering, distance calculation, and interactive lists.

Why use Mapbox Store Locator Patterns on TypingMind?

Because you install it once and use it with any model. Mapbox Store Locator Patterns is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Mapbox Store Locator Patterns in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mapbox/mapbox-agent-skills/tree/main/skills/mapbox-store-locator-patterns. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Mapbox Store Locator Patterns?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Mapbox Store Locator Patterns?

As many as you like. As long as a model supports skills, you can use Mapbox Store Locator Patterns with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Mapbox Store Locator Patterns AI skill free?

Yes. It is published on GitHub by mapbox under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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