Damage Restoration Locations
11,809 US damage restoration businesses, from national chains to single independent shops, 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 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Specialty Abatement Services | 260 Rawls Springs Loop Rd | Hattiesburg | MS | 39402 | (601) 264-5550 | ad8685b9-6f7d-48b5-8afd-3dae5831971d | damage_restoration | |services_and_business|home_service|damage_restoration| | home_service | open | 0.92 | Microsoft | 562949966202567 | Microsoft:562949966202567|Overture-signals:7cae7e72-425b-48f1-8f55-fbe2398019a6 | 2026-08-10 | Overture Maps Foundation, CDLA-Permissive-2.0 | unknown | name: no premises word; website: blank; category: damage_restoration names a business, not premises | 31.364826 | -89.365288 | |||||||
| Superior Cleaning & Restoration Inc. | 32110 Ranch Rd | Homeland | CA | 92548 | (951) 221-3203 | 03750d1e-1efb-4729-b2ba-fe119048631f | damage_restoration | |services_and_business|home_service|damage_restoration| | home_service | open | 0.92 | Microsoft | 1407374884509553 | Microsoft:1407374884509553|Overture-signals:8ab286fb-bdab-429b-adf7-4f0920f3308a | 2026-08-10 | Overture Maps Foundation, CDLA-Permissive-2.0 | unknown | name: no premises word; website: blank; category: damage_restoration names a business, not premises | 33.746637 | -117.100746 | |||||||
| Reichert & Sons Painting | 6996 Wyndham Way | Woodbury | MN | 55125 | (651) 738-3747 | https://reichertpaint.com/ | cf843922-0619-41b2-9cb7-1c4a8e68d741 | damage_restoration | |services_and_business|home_service|damage_restoration| | home_service | open | 0.92 | Microsoft | 562949967723656 | Microsoft:562949967723656|Overture-signals:ca71157c-e782-4819-b8ab-4dbde7ca0efc | 2026-08-10 | Overture Maps Foundation, CDLA-Permissive-2.0 | unknown | name: no premises word; website: none in its path; category: damage_restoration names a business, not premises | 44.904667 | -92.957695 |
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/.
Using ChatGPT, Claude or an API?
Ask this list a question with a link
Using ChatGPT or Claude? Tell it to answer from locationlists.com/find — no account, no connector.
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:
- The whole list: add a city, state, ZIP code or distance:
https://locationlists.com/find?dataset=damage-restoration-locations
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Every answer shows its exact price before you pay, by card, no account; the whole list is $61.46, we email the file when it's built (about 2 minutes). Counts, previews and comparisons with other lists are free.
For developers
Dataset slug damage-restoration-locations. Machine-readable record: dataset.json. Without a connector, every one of these answers comes from a link: https://locationlists.com/find?dataset=damage-restoration-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).