MFNY Retailers
United States · 504 locations
504 stores that carry MFNY (504 in the US): every store on MFNY's own store locator on mfny.co. Name, address, phone, website and the locator's own store details.
The file has all 504 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
≡Sample Data Preview
| store name | address | city | state | zip | phone | website | brand | store id | phone source | website source | status | directions url | brand locator store id | brand locator url | brand locator address | updated date | is chain | chain name | chain store count | overture place id | overture name | overture category | overture brand | overture match meters | naics code | naics title | sic code | sic title | industry source | geo precision | county | county fips | county note | address quality | country | latitude | longitude | source | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 202 Cannabis Co | 81 W Ramapo Rd Unit 1 | Haverstraw | NY | 10923 | (845) 915-7003 | https://202cannabisco.com/shop/categories/all?search=mfny | MFNY | 168adc6548bdea-67099043 | Overture Maps place | Brand store locator | Listed | https://www.google.com/maps/dir/?api=1&destination=41.196383,-74.010206 | 67099043 | https://www.mfny.co/where-to-buy | 81 W Ramapo Rd Unit 1, Haverstraw, New York, 10923 | 2026-10-17 | N | d1f22495-63eb-4d21-8a1e-5561f460fcfa | 202 Cannabis Co | cannabis_clinic | 2 | source | Rockland County | 36087 | complete | US | 41.196383 | -74.010206 | MFNY store locator | ||||||||||
| Chesterfield Cannabis Co | 89 Kent St | Keeseville | NY | 12944 | (518) 834-0046 | https://chesterfieldcannabisco.com/shop/?brand=MFNY | MFNY | 168adc6548bdea-67099238 | Overture Maps place | Brand store locator | Listed | https://www.google.com/maps/dir/?api=1&destination=44.50471,-73.478915 | 67099238 | https://www.mfny.co/where-to-buy | 89 Kent St, Keesville, New York, 12944 | 2026-10-17 | N | 35cf2978-4460-4c54-98ef-b3034920e73b | Chesterfield Cannabis Co. | cannabis_clinic | 4 | source | Essex County | 36031 | ZIP 12944 spans 2 counties; assigned to the county holding 88% of its land area | complete | US | 44.50471 | -73.478915 | MFNY store locator | |||||||||
| Gotham Chelsea | 146 10th Ave | New York | NY | 10011 | https://gotham.nyc/menu/?search=mfny | MFNY | 168adc6548bdea-67099199 | Brand store locator | Listed | https://www.google.com/maps/dir/?api=1&destination=40.745211,-74.005609 | 67099199 | https://www.mfny.co/where-to-buy | 146 10th Ave, New York, New York, 10011 | 2026-10-17 | N | source | New York County | 36061 | complete | US | 40.745211 | -74.005609 | MFNY store locator | ||||||||||||||||
| LeFlora Cannabis | 111 Fulton St | New York | NY | 10038 | https://www.lefloracannabis.com/brand/MFNY | MFNY | 168adc6548bdea-67099225 | Brand store locator | Listed | https://www.google.com/maps/dir/?api=1&destination=40.709833,-74.006805 | 67099225 | https://www.mfny.co/where-to-buy | 111 Fulton St, New York, New York, 10038 | 2026-10-17 | N | 1393d773-0b83-4250-873a-1a30a62234a9 | Le Flora Cannabis Store | cannabis_dispensary | 40 | 459991 | Tobacco, Electronic Cigarette, and Other Smoking Supplies Retailers | 5999 | Miscellaneous Retail Stores, NEC | Overture category of the matched place | source | New York County | 36061 | complete | US | 40.709833 | -74.006805 | MFNY store locator | |||||||
| Sofaclub | 229 Avenue B NY | New York | NY | 10009 | https://www.sofaclub.nyc/menu/brands/MFNY | MFNY | 168adc6548bdea-67099195 | Brand store locator | Listed | https://www.google.com/maps/dir/?api=1&destination=40.729211,-73.978063 | 67099195 | https://www.mfny.co/where-to-buy | 229 Avenue B NY, New York, New York, 10009 | 2026-10-17 | N | source | New York County | 36061 | complete | US | 40.729211 | -73.978063 | MFNY store locator |
{}What's in each row
| Field | What it is | Rows filled |
|---|---|---|
| brand | The brand whose store locator lists the store | 100% |
| store | Store id (unique per place in this file) | 100% |
| store | Store name as the brand's locator lists it | 100% |
| address | Street address | 100% |
| city | City | 100% |
| state | State or province code (US always; outside the US where the locator gives one) | 100% |
| zip | ZIP or postal code | 100% |
| country | Two-letter country code | 100% |
| latitude | Latitude | 100% |
| longitude | Longitude | 100% |
| phone | Store phone | 46% |
| phone | Where the phone came from: the brand's store locator, or the matched Overture place | 46% |
| website | Store website | 86% |
| website | Where the website came from: the brand's store locator, or the matched Overture place | 86% |
| status | Listed | 100% |
| directions | Google Maps directions link | 100% |
| brand | The store's id on the brand's locator | 100% |
| brand | The brand's store locator page | 100% |
| brand | The address as the brand's locator writes it in one line | 100% |
| source | Source of the row | 100% |
| updated | Date the brand's locator was read | 100% |
| is | Y when 5 or more stores in these brand lists carry the same store name | 100% |
| chain | Chain name | 4% |
| chain | Stores with that chain name across these brand lists | 4% |
| overture | Overture Maps place id of the matched place (join key to Overture data) | 49% |
| overture | Name of the matched Overture place | 49% |
| overture | Overture category of the matched place | 40% |
| overture | Brand of the matched Overture place | 1% |
| overture | Distance between the store and the matched Overture place, in metres | 49% |
| naics | NAICS 2022 code | 10% |
| naics | NAICS title | 10% |
| sic | SIC code | 10% |
| sic | SIC title | 10% |
| industry | Where the industry code came from | 10% |
| geo_ | How the map point was set | 100% |
| county | US county (from the store's coordinates) | 100% |
| county_ | US county FIPS code | 100% |
| county_ | Set when the ZIP spans counties | 9% |
| address_ | complete, no house number, po box, missing city or zip or missing | 100% |
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 17, 2026
Snapshot built
40 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 MFNY Retailers and give it this page: it can open https://locationlists.com/find?dataset=mfny-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:
- Within 25 miles of New York, NY, the busiest area: https://locationlists.com/find?dataset=mfny-retailers&near=New+York+NY&radius=25
- Within a 30-minute drive of New York, NY: https://locationlists.com/find?dataset=mfny-retailers&near=New+York+NY&drive=30
- Every Nicotine, Vape & Cannabis list combined, within 25 miles of New York, NY: https://locationlists.com/find?category=nicotine-vape-and-cannabis&near=New+York+NY&radius=25
- Each one's nearest Grabba Leaf Retailers, in New York, with miles: https://locationlists.com/find?dataset=mfny-retailers&state=NY&relate=nearest&k=1&b.dataset=grabba-leaf-retailers&b.state=NY
- The whole list: add a city, state, ZIP code or distance:
https://locationlists.com/find?dataset=mfny-retailers - In plain words: "MFNY Retailers within 25 miles of New York, NY": https://locationlists.com/find?q=MFNY+Retailers+within+25+miles+of+New+York%2C+NY
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 MFNY Retailers list.Your assistant will walk you through setup and show you the price before you pay.
For developers
At 504 records this dataset is not sold by the row — buy the file. Without a connector, open https://locationlists.com/find?dataset=mfny-retailers. An agent connected to https://locationlists.com/mcp can still search it, read a free sample file of up to 10 rows and buy the whole file itself. How agent purchasing works
?Frequently Asked Questions
Where does this data come from?
From MFNY's own store locator on mfny.co. We read every store on its map on 2026-10-17. 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?
No. Every store in this list is in the US.
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?
234 of the 504 stores have a phone, and 431 of the 504 have a website.