Foursquare Scraper — Venue & Places Discovery

Discover venues and places worldwide with rich location data. Search cafes, restaurants, hotels, shops, hospitals, and 35+ other venue types by keyword, category, or geographic coordinates. Powered by OpenStreetMap data — free, global, and no API key required.

What it does

• Search by keyword — find any venue by name (e.g., "Starbucks", "pizza", "coworking space")
• Browse by category — list all cafes, restaurants, hotels, gyms, museums, etc. near a location
• Trending venues — popular tourist and landmark venues in any area
• Returns rich metadata: address, phone, website, opening hours, cuisine type, wheelchair access, payment methods, and more

Input

Field	Type	Description
mode	select	search (default), byCategory, trending
searchQuery	string	Keyword to search (e.g., coffee shop, Marriott), used with mode=search. Optional — leave blank to return all named venues near the location
near	string	City or place name (e.g., New York, London, Tokyo)
latitude	number	Latitude (alternative to near)
longitude	number	Longitude (alternative to near)
venueCategory	select	Category filter: cafe, restaurant, bar, hotel, museum, etc.
radius	integer	Search radius in meters (100–50000, default 5000)
includeNodes	boolean	Include point features (default true)
includeWays	boolean	Include building-footprint features (default false)
maxItems	integer	Max results (1–500, default 50)

Example inputs

Search coffee shops in New York:

{
  "mode": "search",
  "searchQuery": "coffee shop",
  "near": "New York",
  "maxItems": 20
}

Browse all restaurants in London:

{
  "mode": "byCategory",
  "venueCategory": "restaurant",
  "near": "London",
  "radius": 3000,
  "maxItems": 50
}

Trending spots in Paris by coordinates:

{
  "mode": "trending",
  "latitude": 48.8566,
  "longitude": 2.3522,
  "radius": 5000,
  "maxItems": 30
}

Output

Each record contains:

Field	Description
venueId	Unique OSM element ID (e.g., node/746176794)
name	Venue name
alternativeName	Alternate/short name, when OSM has one
primaryCategory	Main category label (e.g., Cafe, Restaurant)
categories	All applicable category labels
address	Street address
city	City
state	State or region
postalCode	Postal/ZIP code
country	Country code
fullAddress	Combined address string
lat	Latitude
lng	Longitude
phone	Phone number
email	Email address
website	Official website URL
facebook	Facebook page URL, when published
instagram	Instagram profile/URL, when published
openingHours	Hours in OSM format (e.g., Mo-Fr 08:00-20:00)
cuisine	Cuisine type for food venues
internetAccess	Internet/Wi-Fi availability, when tagged
brand	Brand/chain name
operator	Operator name
description	Free-text description, when published
wheelchairAccess	Wheelchair accessibility (yes/limited/no)
paymentMethods	Accepted payment methods
outdoorSeating	Outdoor seating, when tagged (e.g. yes, sidewalk, garden)
takeaway	Take-away / to-go availability, when tagged (yes/no/only)
delivery	Delivery availability, when tagged (yes/no/only)
wikipedia	Linked Wikipedia article, when tagged
wikidata	Linked Wikidata ID, when tagged
venueUrl	OpenStreetMap page URL
sourceUrl	Source URL
scrapedAt	UTC timestamp
recordType	Always venue

Sample output record

{
  "venueId": "node/746176794",
  "name": "Starbucks",
  "primaryCategory": "Cafe",
  "categories": ["Cafe", "Coffee Shop"],
  "address": "2525 Broadway",
  "city": "New York",
  "state": "NY",
  "postalCode": "10025",
  "country": "US",
  "lat": 40.7938,
  "lng": -73.9728,
  "phone": "+1 212-000-0000",
  "website": "https://www.starbucks.com",
  "openingHours": "Mo-Su 06:00-22:00",
  "cuisine": "Coffee Shop",
  "brand": "Starbucks",
  "wheelchairAccess": "yes",
  "paymentMethods": ["credit cards", "debit cards"],
  "venueUrl": "https://www.openstreetmap.org/node/746176794",
  "sourceUrl": "https://www.openstreetmap.org/node/746176794",
  "scrapedAt": "2026-06-30T10:00:00+00:00",
  "recordType": "venue"
}

Supported categories

cafe, restaurant, bar, nightclub, hotel, shop, supermarket, pharmacy, bank, atm, hospital, cinema, theatre, museum, library, place_of_worship, school, university, fuel, parking, gym, spa, beauty_salon, fast_food, pub, food_court, ice_cream, bakery, bicycle_rental, car_rental, taxi, bus_station, train_station, airport, ferry_terminal, post_office, police, fire_station, embassy

Frequently Asked Questions

How does this work? This actor uses OpenStreetMap's Overpass API to query venue data. Nominatim is used to geocode city names to coordinates. Both services are free and require no API key.

Is there a usage limit? OpenStreetMap services impose soft rate limits. The actor handles this automatically with retries and delays. For large-scale queries, reduce maxItems or narrow your radius.

How current is the data? OpenStreetMap data is community-maintained and updated continuously. Most venues in major cities have recent data.

Can I search globally? Yes — the near field accepts any city or place name worldwide: "Tokyo", "Dubai", "Buenos Aires", etc.

What's the difference between modes?

• search: Best when you know the venue name or keyword. Searches by name across all types.
• byCategory: Best when you want all venues of a specific type (e.g., all hospitals).
• trending: Best for discovering tourist attractions, historic sites, and popular spots.

Why might some venues be missing a phone or website? OpenStreetMap data coverage varies. Smaller or newer venues may have fewer details. The actor only returns fields that are available in the data.