OpenStreetMap Places Scraper — POIs by City & Category

Get every café, restaurant, hotel, shop, clinic, gym, coworking space — or any other kind of place — that OpenStreetMap has for a city, a neighbourhood or a map box. Each place comes as a clean row with name, category, brand, street address, coordinates, opening hours, website, Wikidata ID and the rest of its OSM tags. Run it again later with Only new places to see what was added.

What you get

Field	What it is
name, nameEn, category, brand, operator, cuisine	what the place is
street, houseNumber, postcode, city, country	address, where mapped
latitude, longitude	position (the centre for buildings and areas)
openingHours, website, wheelchair, wikidata	details
otherTags	every other OSM tag, e.g. outdoor_seating, internet_access, diet:vegan
osmType, osmId, url, location, isNewSinceLastRun	the OSM object, the area searched, and whether it is new since your last run

Phone numbers and email addresses are not collected.

Categories ready to pick: cafe, restaurant, bar, pub, fast-food, hotel, hostel, supermarket, convenience, bakery, pharmacy, hospital, clinic, dentist, doctors, bank, atm, fuel, ev-charging, parking, school, university, library, gym, coworking, museum, attraction, hairdresser, beauty, car-repair, clothes, electronics, real-estate, it-company, veterinary — or give any OSM tag such as shop=bicycle or craft=brewery.

Use it for

• Market and location research — how many cafés, gyms or clinics a district has, and which brands
• Maps and apps — a clean list of places with coordinates and opening hours
• Site selection and competitor mapping — every competitor location in a city
• Data enrichment — Wikidata IDs and websites for brand locations

Input

{ "locations": ["Brooklyn, New York", "Shibuya, Tokyo"], "categories": ["cafe", "coworking"], "tags": ["shop=bakery"] }

Measured on October 7, 2026: cafés, coworking spaces and bakeries in Shibuya and a box over central London — 600 places in 20 seconds. Coverage is as good as OpenStreetMap's volunteers have made it, which varies by city.

Data © OpenStreetMap contributors, available under the Open Database License (ODbL). If you publish the data, credit OpenStreetMap — see openstreetmap.org/copyright. Place names are looked up with Nominatim and places are read with the Overpass API, both public and free; large areas with many categories can take a while.

Pricing

$1.00 per 1,000 places, plus $0.01 per run. Error rows and places left out by your filters are free. The $0.01 run-start fee is the one charge every run pays, even one that returns nothing.

For AI agents

{"locations": ["Lisbon"], "categories": ["coworking"]} returns Lisbon's coworking spaces with coordinates. Rows have type: place or error.

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