This POI API returns points of interest for any area as clean JSON: name, category, address, coordinates, phone, website, rating, review count, opening hours. One credit per place returned.
The places as CSV first, ready for a map layer or a database:
Sample rows as CSV, exactly as exported · phones unmasked in the API response
| name | category | address | lat | lng | phone | rating | reviews |
|---|---|---|---|---|---|---|---|
| Storyville Coffee Pike Place | Coffee shop | 94 Pike St Top floor Suite 34, Seattle, WA 98101 | 47.60895 | -122.3404309 | (206) 780-57•• | 4.6 | 3124 |
| Piedmont Cafe | Coffee shop | 1215 Seneca St Ste 100, Seattle, WA 98101 | 47.6115511 | -122.3242818 | (206) 659-98•• | 4.8 | 290 |
| Overcast Coffee | Coffee shop | 1517 12th Ave Ste 100, Seattle, WA 98122 | 47.6146106 | -122.3171338 | (206) 588-26•• | 4.7 | 298 |
| Coffee TAB | Coffee shop | 211 Lenora St Suit A, Seattle, WA 98121 | 47.6125094 | -122.3427810 | (425) 243-73•• | 4.7 | 603 |
| Mintish Coffee House | Coffee shop | 515 Harvard Ave E #121, Seattle, WA 98102 | 47.6236898 | -122.3222815 | (206) 779-97•• | 5 | 1142 |
| Drip Drip coffeehouse | Coffee shop | 355 15th Ave, Seattle, WA 98122 | 47.6058835 | -122.3131162 | (206) 485-70•• | 4.5 | 339 |
And one point of interest as JSON:
Every point of interest comes complete, so you can build a map layer, a directory, or a dataset with no second call.
Records are pulled fresh at query time, not served from an aging file, and each carries a scrapedAt timestamp so you always know how fresh a row is.
The same endpoint scales from a single lookup to full POI data coverage of a city or vertical.
Need every coffee shop in Seattle, every pharmacy in Texas, or every gym in the top 50 metros? Loop the endpoint over your categories and cities and you have a POI database that is as fresh as the day you pulled it, in the same schema every time. For very large footprints, ready-made datasets are the bulk lane: the same records, packaged, without running the pulls yourself.
The classic POI options are a licensed annual file or Google's official Places API. Different trade-offs on both.
| Licensed POI file | Google Places API | CrustAPI | |
|---|---|---|---|
| Freshness | Ages between releases | Fresh | Fresh at query time |
| Pricing shape | Annual license | Per call by SKU tier; Text Search Pro is $32 / 1,000 calls | 1 credit per place returned |
| Fields per record | Varies by vendor | Gated by SKU tier | All fields, every time |
| Entry cost | Quote | Free monthly threshold, then per call | 3,000 free credits / month |
The Places API figure is Google's published Text Search Pro rate at the base usage tier, from Google's usage and billing page, checked July 27, 2026. Note it bills per call while we bill per place returned, so compare on your own query shapes.
What the classic options cost to even start, against the metered route.
When a licensed POI file is the better pick: navigation-grade attributes, building polygons, indoor mapping, or a redistribution license for shipping the data inside your own product. Those are file-vendor strengths. This API is for live, business-level POI data you query on demand.
Simple meter, no subscription, no quote call.
Place searches bill 1 credit per business returned, and a search that returns nothing costs nothing. Start free with 3,000 credits every month, no card. Paid packs are prepaid and self-serve: 25k for $49 · 100k for $149 · 500k for $549 · 2.5M for $1,999 · up to 250M, ex-tax. That is about $1.96 per 1,000 records at the entry pack, falling to roughly $0.40 per 1,000 at the largest. Credits never expire.
Related: Google Maps scraper API · Business leads API · Google Places API alternative · Restaurant API · Datasets
Run one category in one city on the free tier and look at what comes back. 3,000 credits, no card.
Get 3,000 free credits