The Gym Kitchen Retailers
1 country · 6,597 locations

6,597 stores that carry The Gym Kitchen (0 in the US): every store on The Gym Kitchen's own store locator on thegymkitchen.com.

More about this list

Name, address, phone, website and the locator's own store details.

6,597Locations
39Data Fields
October 16, 2026File built

The file has all 6,597 locations in one download. Building the same list by searching one area at a time tends to miss places, and a missed place looks like a gap in coverage that is not really there.

Need just some of them? Ask in your own words.

●Where the rows are

Map of where the The Gym Kitchen Retailers are
One dot for every ZIP code with at least one location. Ask above for any part of it: a state, a city, a distance.

≡Sample Data Preview

the-gym-kitchen-retailers.csvscroll →UTF-8
store nameaddresscityzipphonewebsitebrandstore idphone sourcewebsite sourcestore typestatusdirections urlbrand locator store idbrand locator urlcountry as publishedupdated datestockist filtersstockist filter idssrc priorityis chainchain namechain store countoverture place idoverture nameoverture categoryoverture brandoverture match metersnaics codenaics titlesic codesic titleindustry sourcegeo precisionaddress qualitycountrylatitudelongitudesource
Co-Op LauncestonNewport Industrial Estate LauncestonPL15 8EXThe Gym Kitchenu15547-156847089400g & 550g Frozen Meals | Grains & Lentils Pouches | Ready to Go WrapsListedhttps://www.google.com/maps/dir/?api=1&destination=50.6403183,-4.35948714156847089https://thegymkitchen.com/pages/store-locator-3UK2026-10-16400g & 550g Frozen Meals | Grains & Lentils Pouches | Ready to Go Wraps17265 | 17267 | 215630Nsourceno_house_numberGB50.6403183-4.35948714The Gym Kitchen store locator
One sample row; the file you buy has all 39 columns.

{}What's in each row

FieldWhat it isRows filled
brandThe brand whose store locator lists the store100%
storeIdStore id (unique per place in this file)100%
storeNameStore name as the brand's locator lists it100%
addressStreet address96%
cityCity26%
zipZIP or postal code100%
countryTwo-letter country code100%
latitudeLatitude100%
longitudeLongitude100%
phoneStore phone46%
phoneSourceWhere the phone came from: the brand's store locator, or the matched Overture place46%
websiteStore website46%
websiteSourceWhere the website came from: the brand's store locator, or the matched Overture place46%
storeTypeThe brand's own tags for the store on its locator (product lines, store types, retailer)99%
statusListed100%
directionsUrlGoogle Maps directions link100%
brandLocatorStoreIdThe store's id on the brand's locator100%
brandLocatorUrlThe brand's store locator page100%
countryAsPublishedThe country as the locator wrote it, where it differs from the code100%
sourceSource of the row100%
updatedDateDate the brand's locator was read100%
stockistFiltersThe locator's filter tags on this store99%
stockistFilterIdsIds of those filter tags99%
src_priorityAnother field the brand's locator publishes for the store: priority100%
isChainY when 5 or more stores in these brand lists carry the same store name100%
chainNameChain name3%
chainStoreCountStores with that chain name across these brand lists3%
overturePlaceIdOverture Maps place id of the matched place (join key to Overture data)47%
overtureNameName of the matched Overture place47%
overtureCategoryOverture category of the matched place47%
overtureBrandBrand of the matched Overture place46%
overtureMatchMetersDistance between the store and the matched Overture place, in metres47%
naicsCodeNAICS 2022 code44%
naicsTitleNAICS title44%
sicCodeSIC code44%
sicTitleSIC title44%
industrySourceWhere the industry code came from44%
geo_precisionHow the map point was set100%
address_qualitycomplete, no house number, po box, missing city or zip or missing100%

Rows filled is measured on every row of the delivered file.

✓Where this data comes from

Each row names the public source it came from, so any record can be checked against where it was published.

October 16, 2026

Snapshot built

39 fields

Columns in the file

Fill measured

On every row of the delivered file

How we build and date every file: methodology.

Using ChatGPT, Claude or an API?

No setup needed. Ask ChatGPT or Claude your question about the The Gym Kitchen Retailers and give it this page: it can open https://locationlists.com/find?dataset=the-gym-kitchen-retailers with the filters you need and show you the count and price.

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.

Links an assistant can open, each showing how many rows match, a few preview rows and the price for just that part:

  • The whole list: add a city, state, ZIP code or distance: https://locationlists.com/find?dataset=the-gym-kitchen-retailers

Optional: connect for repeat use or wallet payments:

Read https://locationlists.com/skill.md and follow the instructions to connect LocationLists. Then show me the The Gym Kitchen Retailers list.

Your assistant will walk you through setup and show you the price before you pay.

For developers

Every step below has a no-connector equivalent: https://locationlists.com/find?dataset=the-gym-kitchen-retailers with the same filters as query parameters.

  1. Connect your agent to https://locationlists.com/mcp (no key, no signup).
  2. Call count_locations with dataset: "the-gym-kitchen-retailers" and any filter — it is free, and returns how many rows match and what they cost.
  3. Fetch the rows with query_locations: $1.19 per 100 rows from this dataset. Above 3,299 rows, buying the whole file is cheaper.

Paid in USDC over x402 — the agent gets an HTTP 402 with the exact price, signs, and retries. Money moves only after rows are delivered, so a failed or empty query costs nothing. Setup for Claude, Cursor and VS Code

?Frequently Asked Questions

Where does this data come from?

From The Gym Kitchen's own store locator on thegymkitchen.com. We read every store on its map on 2026-10-16. A store the map shows twice (same name and address) is one row.

What is one row?

One store on the brand's locator, with the brand's own tags for it (storeType) and any custom fields the locator shows.

Does it include stores outside the US?

Yes. 6,597 of the 6,597 stores are outside the US, across 1 country. Filter on country for one market.

Where do websites and phones come from?

From the brand's locator where it gives them. Otherwise from the Overture Maps place at the same spot with the same name. phoneSource and websiteSource say which.

How complete are phones and websites?

3,002 of the 6,597 stores have a phone, and 3,040 of the 6,597 have a website.

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