Skylar Laundromat Locations
334 US Skylar Laundromat locations, with address, phone, website and map coordinates.
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Sample data
| name | address | city | state | zip | phone | website | overture id | brand | brand id | wikidata | category | category path | basic category | social | operating status | confidence | source dataset | source record id | source ids | source updated | data license | location type | location type confidence | location type basis | latitude | longitude | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Three Boys Laundromat | 297 E Meadow Ave | East Meadow | NY | 11554-2937 | (718) 954-0535 | https://www.threeboyslaundry.com/ | 99f65749-28ce-4455-a6c5-ccfe35d9eba1 | Skylar Laundromat | Nskylarlaundromat | laundromat | |services_and_business|laundry_service|laundromat| | laundry_service | vincenuzz@gmail.com | https://www.facebook.com/336431100104599 | open | 0.92 | meta | 336431100104599 | meta:336431100104599|Overture-signals:1549af84-e9e8-41cc-a095-b4558bc784e7 | 2026-08-10 | Overture Maps Foundation, CDLA-Permissive-2.0 | unknown | name: no premises word; website: none in its path; category: laundromat names a business, not premises | 40.716579 | -73.561329 | ||
| Brooklyn Tub Laundromat | 5101 Ritchie Hwy | Brooklyn | MD | 21225 | (443) 948-7123 | e6d3e2c6-1c3d-47ee-aa5b-33587077e406 | Skylar Laundromat | Nskylarlaundromat | laundromat | |services_and_business|laundry_service|laundromat| | laundry_service | https://www.facebook.com/351269635252428 | open | 0.99 | meta | 351269635252428 | meta:351269635252428|Overture-signals:eec337e8-232e-4d4a-b826-43794ecd35ea | 2026-08-10 | Overture Maps Foundation, CDLA-Permissive-2.0 | unknown | name: no premises word; website: blank; category: laundromat names a business, not premises | 39.222925 | -76.613029 | ||||
| The Laundromat | 263 S Church St | Ripley | WV | 25271 | (304) 761-1210 | https://thelaundromatwv.com/ | 7e0c03cb-8218-496b-9a0a-3f2bcbdbe183 | Skylar Laundromat | Nskylarlaundromat | laundromat | |services_and_business|laundry_service|laundromat| | laundry_service | acwpropertieswv@gmail.com | https://www.facebook.com/107586098607920 | open | 0.92 | meta | 107586098607920 | meta:107586098607920|Overture-signals:5129242d-cc93-4f70-9181-3ca8c7ac3cf3 | 2026-08-10 | Overture Maps Foundation, CDLA-Permissive-2.0 | unknown | name: no premises word; website: none in its path; category: laundromat names a business, not premises | 38.813173 | -81.70805 |
What's in each row
| Field | What it is |
|---|---|
| overture_ | Map data id for the place, stable across monthly releases |
| name | Business name |
| brand | Brand or chain name, when the place belongs to one |
| brand_ | Our id for that brand (its Wikidata id where one exists) |
| wikidata | Wikidata id of the brand |
| category | Kind of place, from the map data |
| category_ | The category with every broader category above it |
| basic_ | A broader, simpler category |
| address | Street address |
| city | City |
| state | State (two-letter code) |
| zip | ZIP code |
| phone | Phone number |
| website | Website |
| Email address | |
| social | Social media page |
| latitude | Latitude |
| longitude | Longitude |
| operating_ | Whether the place is open, where the source says; closed places are left out of the list |
| confidence | How sure the map data is that the place exists (0 to 1) |
| source_ | Which source contributed the record |
| source_ | The record's id in that source |
| source_ | Every source record merged into this row |
| source_ | When the source last updated the record |
| data_ | The license the row is published under |
| location_ | Kind of premises: store, office, branch, warehouse and so on, read from the name, website and category |
| location_ | How sure the location type is (0 to 1) |
| location_ | What the location type was read from |
Source & license
Open map data from the Overture Maps Foundation, release of August 2026, refreshed monthly. Closed and low-confidence places are removed and duplicates within 50 meters merged. Contains data from Overture Maps Foundation (https://overturemaps.org), Places theme, licensed CDLA-Permissive-2.0 (https://cdla.dev/permissive-2-0/); some sources are Apache-2.0. See https://docs.overturemaps.org/attribution/.
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How assistants ask
No connector needed. Any AI assistant can answer from this site with a web link, no connector, no account: open https://locationlists.com/find with the question as query parameters.
If a question needs filtering, distance, drive time, combining lists or a price, open a /find link: either put the question itself in q=, or build the structured link. The answer does not need an API, a connector or an account.
Simplest, the question itself: https://locationlists.com/find?q=<the question in plain words>
Or set the parts yourself: https://locationlists.com/find?dataset=<slug>&state=<ST>&city=<city>&county=<county>&zip=<zip>&near=<place or zip>&radius=<miles>&drive=<minutes>&where=<column>:<op>:<value>&total=<rows>
Leave out what the question does not need. Use radius for straight-line miles or drive for minutes of driving (5 to 60), not both; near can name several places separated by | to reach from any of them. To ask about several lists at once, use datasets with two or more names, or category with a kind of business. To compare two lists, add relate=nearest and the other list with b. in front of its parameters. To count by area, use areas=county (or zip, state, metro). To keep only places whose county, ZIP code, metro area or state meets a Census figure, add area_where (for example county:population>1000000); with areas, per=100000 gives counts per 100,000 residents.
Open one of these to see how many places match, a few preview rows and the price for just those rows:
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https://locationlists.com/find?dataset=skylar-laundromat-locations
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For developers
Dataset slug skylar-laundromat-locations. Machine-readable record: dataset.json. Without a connector, every one of these answers comes from a link: https://locationlists.com/find?dataset=skylar-laundromat-locations. Works in every MCP tool and the x402 query API like any other dataset (count_locations, get_sample, query_locations, relate_locations, count_by_area, cotenancy).