Foursquare Scraper — Chain Locations by City

What does Foursquare Scraper do?

Foursquare Scraper extracts structured chain location data from foursquare.com — including contact details, location data, and seller ratings. It supports keyword search, location filters, and controllable result limits, so you can run the same query consistently over time. The actor also offers detail enrichment (contact information) where the source provides them.

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Key features

• ⭐ Ratings: rating (Foursquare's 0-10 score) for every chain location that has one.
• 🏘️ Address: address, city, state and postalCode as separate fields for every chain location that lists them.
• 📇 Contact details: phone and website where the chain location publishes them.
• 🏷️ Brand and identifiers: brand on every chain location, ready to join against your own catalog.
• 🗂️ Category path: category place each chain location in foursquare.com's own category tree.
• 🔍 Brand + city search: name a brand in query and a city in location to get that chain's locations in the city — up to 30 per city, as foursquare.com lists them. Add more cities for wider coverage.
• 🧭 Radius filter: keep only the city's locations within radiusKm of lat/lon. It filters the named city's results; it does not search beyond it.
• 🔗 Paste-mode: paste foursquare.com URLs into startUrls to scrape exactly the pages you picked in the browser.
• 📋 Detail fields: includeDetails adds any extra fields foursquare.com shows anonymously beyond the city listing. Venue pages currently require login, so today every record comes from the listing (detailFetched: false).
• ♻️ Incremental mode: recurring runs emit only directory entries that are new or updated — keep your supplier-outreach lists fresh without re-fetching the full directory. Saves 80–95% on weekly syncs.
• 🔔 Notifications: Telegram, Slack, Discord, WhatsApp Cloud API, and generic webhook out of the box. Pair with incremental for daily new-listing alerts without pipeline glue.

What data can you extract from foursquare.com?

Each result includes Core chain location fields (venueId, name, brand, queryCity, neighborhood, address, crossStreet, and city, and more), detail fields when enrichment is enabled (detailFetched), and contact information (phone and formattedPhone). In standard mode, all fields are always present — unavailable data points are returned as null, never omitted. In compact mode, only core fields are returned.

Enable detail enrichment in the input to get richer fields such as contact information where the source provides them.

Input

The main inputs are a search keyword, an optional location filter, and a result limit. Additional filters and options are available in the input schema.

Key parameters:

• query — Brand or chain whose locations you want (e.g. "starbucks", "mcdonalds", "cvs-pharmacy"). Use a JSON array for several brands, e.g. ["starbucks","dunkin"].
• location — City whose locations of that brand you want (e.g. "new york city", "chicago", "london"). Required with Brand: foursquare.com lists a brand's locations per city (up to 30 per city). Use a JSON array for several cities, e.g. ["new york city","boston"].
• maxResults — Maximum total venues to return (0 = unlimited). foursquare.com shows up to 30 venues per brand and city, so add cities to get more. (default: 100)
• startUrls — Paste brand locations URLs, one city per URL (e.g. https://foursquare.com/locations/starbucks/new-york-city). Each URL becomes its own task; results are merged and deduped across all URLs. When provided, startUrls REPLACE the brand/city fields (unsupported URLs are skipped, and if none is supported the run stops with an input error). (default: [])
• includeDetails — Enrich each venue with any extra details the source exposes beyond the listing itself. Venue pages currently require login on foursquare.com, so results today come from the city listing. (default: true)
• compact — Core fields only (for AI-agent/MCP workflows). (default: false)
• excludeEmptyFields — Drop null, empty-string, and empty-array fields from each record before push. Smaller payloads for AI agents and dashboards. (default: false)
• incrementalMode — Compare against previous run state and return only new or changed venues. stateKey is optional — defaults to a value derived from your search inputs (brands, cities, startUrls) so different searches never share state. (default: false)
• stateKey — Optional. Stable identifier for the tracked search universe. Leave empty to auto-generate from search inputs.
• skipReposts — When incremental, skip venues whose content matches an expired venue from a prior run (cross-run duplicate detection). (default: false)
• emitUnchanged — When incremental, also emit venues that haven't changed. (default: false)
• emitExpired — When incremental, also emit venues no longer listed. (default: false)
• ...and 17 more parameters

Input examples

Basic search — Keyword-driven search scoped to a city with a tight radius.

→ Full payload per result — all standard fields populated where the source provides them.

{
  "query": "starbucks",
  "location": "new york city",
  "radiusKm": 25,
  "maxResults": 50
}

Incremental tracking — Only emit chain locations that changed since the previous run with this stateKey.

→ First run builds the baseline state. Subsequent runs emit only records that are new or whose tracked content changed. Set emitUnchanged: true to include unchanged records as well.

{
  "query": "starbucks",
  "maxResults": 200,
  "incrementalMode": true,
  "stateKey": "starbucks-tracker"
}

Compact output for AI agents — Return only core fields for AI-agent and MCP workflows.

→ Small payload with the most important fields — ideal for piping into LLMs without token overhead.

{
  "query": "starbucks",
  "maxResults": 50,
  "compact": true
}

Output

Each run produces a dataset of structured chain location records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console.

Example chain location record

{
  "venueId": "51964c1a498eeaca10e9ea4c",
  "name": "Starbucks",
  "brand": "starbucks",
  "queryCity": "new york city",
  "neighborhood": "Upper East Side",
  "address": "822 Lexington Ave",
  "crossStreet": "at E 63rd St",
  "city": "New York",
  "state": "NY",
  "postalCode": "10065",
  "country": "United States",
  "latitude": 40.76462850100318,
  "longitude": -73.96668685798046,
  "phone": "2125720984",
  "formattedPhone": "(212) 572-0984",
  "website": "https://www.starbucks.com/store-locator/store/116566",
  "category": "Coffee Shop",
  "rating": 6,
  "ratingSignals": 213,
  "verified": true,
  "isOpen": true,
  "hoursStatus": "Open until 9:00 PM",
  "hours": "Mon–Fri: 5:00 AM–9:30 PM; Sat: 5:00 AM–9:00 PM; Sun: 5:30 AM–8:00 PM",
  "popularHours": "Today: 8:00 AM–6:00 PM; Sun: 9:00 AM–6:00 PM; Mon: 8:00 AM–6:00 PM; Tue: 5:00 AM–Noon, 2:00 PM–7:00 PM; Wed: 8:00 AM–6:00 PM; Thu: 5:00 AM–7:00 PM; Fri: 7:00 AM–6:00 PM",
  "menuUrl": "http://www.starbucks.com/menu",
  "directionsUrl": "https://www.google.com/maps/dir/?api=1&destination=40.76462850100318%2C-73.96668685798046",
  "tipText": "Service is slow but they are friendly",
  "tipAuthor": "Gigi Dennis",
  "tipUrl": "https://app.foursquare.com/item/51a68495498eecef60ee3e14",
  "imageUrls": [
    "https://fastly.4sqi.net/img/general/original/9419164_GCuwOhBiLXLLH_pjlhZEOkoU9OlPLzajKnnTZi8lzeA.jpg"
  ],
  "venueUrl": "https://app.foursquare.com/v/starbucks/51964c1a498eeaca10e9ea4c",
  "sourceUrl": "https://foursquare.com/locations/starbucks/new-york-city",
  "sourceTotalLocations": 315,
  "scrapedAt": "2026-10-10T14:30:00.394Z",
  "checkinsCount": 5580,
  "usersCount": 2512,
  "tipCount": 25,
  "countryCode": "US",
  "timeZone": "America/New_York",
  "categoryIds": [
    "4bf58dd8d48988d1e0931735"
  ],
  "chainIds": [
    "556f676fbd6a75a99038d8ec"
  ],
  "twitter": "starbucks",
  "facebook": "22092443056",
  "hoursTimeframes": [
    {
      "days": "Mon–Fri",
      "open": [
        {
          "renderedTime": "5:00 AM–9:30 PM"
        }
      ]
    },
    {
      "days": "Sat",
      "includesToday": true,
      "open": [
        {
          "renderedTime": "5:00 AM–9:00 PM"
        }
      ]
    },
    {
      "days": "Sun",
      "open": [
        {
          "renderedTime": "5:30 AM–8:00 PM"
        }
      ]
    }
  ],
  "popularTimeframes": [
    {
      "days": "Today",
      "includesToday": true,
      "open": [
        {
          "renderedTime": "8:00 AM–6:00 PM"
        }
      ]
    },
    {
      "days": "Sun",
      "open": [
        {
          "renderedTime": "9:00 AM–6:00 PM"
        }
      ]
    },
    {
      "days": "Mon",
      "open": [
        {
          "renderedTime": "8:00 AM–6:00 PM"
        }
      ]
    },
    {
      "days": "Tue",
      "open": [
        {
          "renderedTime": "5:00 AM–Noon"
        },
        {
          "renderedTime": "2:00 PM–7:00 PM"
        }
      ]
    },
    {
      "days": "Wed",
      "open": [
        {
          "renderedTime": "8:00 AM–6:00 PM"
        }
      ]
    },
    "... 2 more items"
  ],
  "instagram": "starbucks",
  "categories": [
    "Coffee Shop"
  ],
  "createdAt": "2013-05-17T15:26:18.000Z",
  "popularStatus": "Likely open",
  "contextLine": "New York, United States",
  "listing_id": "51964c1a498eeaca10e9ea4c",
  "url": "https://app.foursquare.com/v/starbucks/51964c1a498eeaca10e9ea4c",
  "portalUrl": "https://app.foursquare.com/v/starbucks/51964c1a498eeaca10e9ea4c",
  "title": "Starbucks",
  "last_modified": "2013-05-17T15:26:18.000Z",
  "image_url": "https://fastly.4sqi.net/img/general/original/9419164_GCuwOhBiLXLLH_pjlhZEOkoU9OlPLzajKnnTZi8lzeA.jpg",
  "raw": {
    "venueId": "51964c1a498eeaca10e9ea4c",
    "name": "Starbucks",
    "brand": "starbucks",
    "queryCity": "new york city",
    "neighborhood": "Upper East Side",
    "address": "822 Lexington Ave",
    "crossStreet": "at E 63rd St",
    "city": "New York",
    "state": "NY",
    "postalCode": "10065",
    "country": "United States",
    "latitude": 40.76462850100318,
    "longitude": -73.96668685798046,
    "phone": "2125720984",
    "formattedPhone": "(212) 572-0984",
    "website": "https://www.starbucks.com/store-locator/store/116566",
    "category": "Coffee Shop",
    "rating": 6,
    "ratingSignals": 213,
    "verified": true,
    "isOpen": true,
    "hoursStatus": "Open until 9:00 PM",
    "hours": "Mon–Fri: 5:00 AM–9:30 PM; Sat: 5:00 AM–9:00 PM; Sun: 5:30 AM–8:00 PM",
    "popularHours": "Today: 8:00 AM–6:00 PM; Sun: 9:00 AM–6:00 PM; Mon: 8:00 AM–6:00 PM; Tue: 5:00 AM–Noon, 2:00 PM–7:00 PM; Wed: 8:00 AM–6:00 PM; Thu: 5:00 AM–7:00 PM; Fri: 7:00 AM–6:00 PM",
    "menuUrl": "http://www.starbucks.com/menu",
    "directionsUrl": "https://www.google.com/maps/dir/?api=1&destination=40.76462850100318%2C-73.96668685798046",
    "tipText": "Service is slow but they are friendly",
    "tipAuthor": "Gigi Dennis",
    "tipUrl": "https://app.foursquare.com/item/51a68495498eecef60ee3e14",
    "imageUrls": [
      "https://fastly.4sqi.net/img/general/original/9419164_GCuwOhBiLXLLH_pjlhZEOkoU9OlPLzajKnnTZi8lzeA.jpg"
    ],
    "venueUrl": "https://app.foursquare.com/v/starbucks/51964c1a498eeaca10e9ea4c",
    "sourceUrl": "https://foursquare.com/locations/starbucks/new-york-city",
    "sourceTotalLocations": 315,
    "scrapedAt": "2026-10-10T14:30:00.383Z",
    "checkinsCount": 5580,
    "usersCount": 2512,
    "tipCount": 25,
    "countryCode": "US",
    "timeZone": "America/New_York",
    "categoryIds": [
      "4bf58dd8d48988d1e0931735"
    ],
    "chainIds": [
      "556f676fbd6a75a99038d8ec"
    ],
    "twitter": "starbucks",
    "facebook": "22092443056",
    "hoursTimeframes": [
      {
        "days": "Mon–Fri",
        "open": [
          {
            "renderedTime": "5:00 AM–9:30 PM"
          }
        ]
      },
      {
        "days": "Sat",
        "includesToday": true,
        "open": [
          {
            "renderedTime": "5:00 AM–9:00 PM"
          }
        ]
      },
      {
        "days": "Sun",
        "open": [
          {
            "renderedTime": "5:30 AM–8:00 PM"
          }
        ]
      }
    ],
    "popularTimeframes": [
      {
        "days": "Today",
        "includesToday": true,
        "open": [
          {
            "renderedTime": "8:00 AM–6:00 PM"
          }
        ]
      },
      {
        "days": "Sun",
        "open": [
          {
            "renderedTime": "9:00 AM–6:00 PM"
          }
        ]
      },
      {
        "days": "Mon",
        "open": [
          {
            "renderedTime": "8:00 AM–6:00 PM"
          }
        ]
      },
      {
        "days": "Tue",
        "open": [
          {
            "renderedTime": "5:00 AM–Noon"
          },
          {
            "renderedTime": "2:00 PM–7:00 PM"
          }
        ]
      },
      {
        "days": "Wed",
        "open": [
          {
            "renderedTime": "8:00 AM–6:00 PM"
          }
        ]
      },
      "... 2 more items"
    ],
    "instagram": "starbucks",
    "categories": [
      "Coffee Shop"
    ],
    "createdAt": "2013-05-17T15:26:18.000Z",
    "popularStatus": "Likely open",
    "contextLine": "New York, United States"
  },
  "listingId": "af8ba99c027e48e1df02e800c70481a7711ef7ccfb6fba125f7ba7354ac47f18",
  "searchQuery": "starbucks",
  "contentQuality": "serp_only",
  "detailFetched": false,
  "source": "foursquare.com"
}

Incremental fields

When incremental mode is on, each record also carries:

• changeType — one of NEW, UPDATED, UNCHANGED, REAPPEARED, EXPIRED. Default output covers NEW / UPDATED / REAPPEARED; set emitUnchanged: true or emitExpired: true to opt into the others.
• isRepost, repostOfId, repostDetectedAt — populated when a new listing matches the tracked content of a previously expired one. Set skipReposts: true to drop detected reposts from the output.

How to scrape foursquare.com

1. Go to Foursquare Scraper in Apify Console.
2. Enter a search keyword and optional location filter.
3. Set maxResults to control how many results you need.
4. Enable includeDetails if you need contact info.
5. Click Start and wait for the run to finish.
6. Export the dataset as JSON, CSV, or Excel.

Use cases

• Extract chain location data from foursquare.com for market research and competitive analysis.
• Monitor new and changed chain locations on scheduled runs without processing the full dataset every time.
• Use structured location data for regional analysis, mapping, and geo-targeting.
• Feed structured data into AI agents, MCP tools, and automated pipelines using compact mode.
• Export clean, structured data to dashboards, spreadsheets, or data warehouses.
• Benchmark seller / dealer reputation using rating fields.

How much does it cost to scrape foursquare.com?

Foursquare Scraper uses pay-per-event pricing. You pay a small fee when the run starts and then for each result that is actually produced.

• Run start: $0.00005 per run
• Per result: $0.00449 per chain location record

Example costs:

• 10 results: $0.045
• 25 results: $0.11
• 100 results: $0.45
• 200 results: $0.9
• 500 results: $2.25

Example: recurring monitoring savings

These examples compare full re-scrapes with incremental runs at different churn rates. Churn is the share of chain locations that are new or whose tracked content changed since the previous run. Actual churn depends on your query breadth, source activity, and polling frequency — the scenarios below are examples, not predictions.

Example setup: 250 chain locations per run, daily polling (30 runs/month). Costs scale linearly with the number of chain locations.

Churn rate	Full re-scrape run cost	Incremental run cost	Savings vs full re-scrape	Monthly cost after baseline
5% — stable niche query	$1.12	$0.06	$1.07 (95%)	$1.69
15% — moderate broad query	$1.12	$0.17	$0.95 (85%)	$5.05
30% — high-volume aggregator	$1.12	$0.34	$0.79 (70%)	$10.11

Full re-scrape monthly cost at the same cadence: $33.68. First month with incremental costs $2.75 / $6.01 / $10.89 for the 5% / 15% / 30% scenarios because the first run builds baseline state at full cost before incremental savings apply.

Platform usage is included in the per-result fee shown above.

FAQ

How many results can I get from foursquare.com?

The number of results depends on the search query and available chain locations on foursquare.com. Use the maxResults parameter to control how many results are returned per run.

Does Foursquare Scraper support recurring monitoring?

Yes. Enable incremental mode to only receive new or changed chain locations on subsequent runs. This is ideal for scheduled monitoring where you want to track changes over time without re-processing the full dataset.

Can I integrate Foursquare Scraper with other apps?

Yes. Foursquare Scraper works with Apify's integrations to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes.

Can I use Foursquare Scraper with the Apify API?

Yes. You can start runs, manage inputs, and retrieve results programmatically through the Apify API. Client libraries are available for JavaScript, Python, and other languages.

Can I use Foursquare Scraper through an MCP Server?

Yes. Apify provides an MCP Server that lets AI assistants and agents call this actor directly. Use compact mode, a single descriptionFormat, and excludeEmptyFields to keep payloads manageable for LLM context windows.

Is it legal to scrape foursquare.com?

This actor extracts publicly available data from foursquare.com. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant.

Your feedback

If you have questions, need a feature, or found a bug, please open an issue on the actor's page in Apify Console. Your feedback helps us improve.

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Getting started with Apify

New to Apify? Create a free account with $5 credit — no credit card required.

1. Sign up — $5 platform credit included
2. Open this actor and configure your input
3. Click Start — export results as JSON, CSV, or Excel

Need more later? See Apify pricing.

Disclaimer

This actor accesses only publicly available data on foursquare.com. You are responsible for how you use the extracted data — in particular any personal information such as names, phone numbers, or email addresses — and for complying with Foursquare's terms of use, applicable data-protection law (including the GDPR where it applies), and the anti-spam rules of your jurisdiction.

This actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Foursquare or any of its subsidiaries. All trademarks mentioned are the property of their respective owners.

Search keywords

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