LocationLists

US business location lists

LocationLists answers questions about where US businesses are, from 1,333 location lists covering 15.7 million places. Most lists come from a company's own store, branch or dealer locator.

What you can ask

How many independent pest control companies are within 25 miles of Dallas?
Example path ·

MCP connector

Server URL: https://locationlists.com/mcp/chatgpt
Login: None
Protocol: MCP 2025-11-25
Instructions: No connector needed: any AI assistant can answer a location question by opening https://locationlists.com/find?q=<the question in plain words> — counts, a preview, a price and a card checkout link. Connect the MCP for repeat use or wallet payments. LocationLists publishes ready-to-use CSV datasets of US (and some Canadian) business locations — every dealer, store or restaurant a brand publishes in its own official locator. NO SETUP NEEDED: every question these tools answer also has a plain web link that any assistant able to open a page can use, with no connector, account or key: https://locationlists.com/find?dataset=<slug>&near=<place or zip>&radius=<miles> (or drive=<minutes>; state=, city=, zip=, where=<column>:<op>:<value>; category= or datasets= to combine lists; total=<rows>). It returns the count, up to 3 fixed sample rows of the lists involved, the price and a Buy link. A connector is never required to get an answer; a one-off question works from the /find link. When a question is genuinely ambiguous the /find answer (and the JSON's clarification field) still carries the best-guess answer, plus a few complete links that each settle one reading: ask your user which they meant, or proceed on the best guess. Use to find datasets (by brand, kind of business or industry), for the full record (fields, counts, coverage, real last-modified date, filterable columns), to show the user real rows, and to count rows matching filters on any column. Link twins: = https://locationlists.com/find?search=<words>; = https://locationlists.com/data/<slug>/dataset.json; and = https://locationlists.com/find?dataset=<slug>&<filters>. compares two lists by distance (link twin: https://locationlists.com/find?dataset=<slug>&relate=nearest&k=1&b.dataset=<other slug>). counts places per county, ZIP, state or metro for up to 4 lists, with has / lacks (link twin: https://locationlists.com/find?areas=county&dataset=<slug>&b.dataset=<other slug>&has=a&lacks=b). Both are free. Every result starts with answer (and often next): plain words and a link, written for a business reader. The technicalDetails field carries tool names, arguments and payment terms for developers and AI agents; anyone may read it. GEOGRAPHY: filter by radius, city or zip (or drive time) with and before buying — e.g. near {place: "Los Angeles, CA", radius_miles: 25} or near {place: "Richmond, VA", drive_minutes: 30} on a list with map coordinates (search results say distanceSearch), or city/state/zip, or where on any column. gives the exact number of matches; with the same filters returns that count plus the list's fixed free sample rows, each marked matches_your_question — the same rows whatever the filter, so they show the real column shape, not a sample of the matches. Both are free, and both return next, which says how to get every matching row. Each brand or chain is its own dataset. To cover a kind of business near one place ("200 restaurants near Chicago"), pass category (a kind of business, an industry, or "retail") or datasets (a list of slugs) and total instead of dataset: and then give one combined answer (counts per dataset, duplicates removed, a preview, one price), and next says how to get the rows as one file. Link twins for the same questions: https://locationlists.com/find?dataset=<slug>&near=Los+Angeles+CA&radius=25, https://locationlists.com/find?dataset=<slug>&near=23219&drive=30, https://locationlists.com/find?category=retail&near=Los+Angeles+CA&radius=25&total=100. Purchases happen on locationlists.com, not in chat. Answers include the exact card price and a locationlists.com link (the link field) where the user sees the answer and can pay for only the matching rows or the whole list. Never tell the user the rows cannot be had: the count, a preview, the price and the link are always available. Never claim a dataset is fresher than its lastModified date. If nothing fits what the user wants, offer : ask before sending, and ask for their email so we can tell them when the list is ready (never invent one). passes a problem or suggestion to the LocationLists team. 's link twin: the "Request it" box at https://locationlists.com after a search.

Tools

Reads data7

Changes data2

Skills

1 in the ChatGPT listing

MCP connector

Server URL

https://locationlists.com/mcp/chatgpt

None

Protocol

MCP 2025-11-25

Instructions

No connector needed: any AI assistant can answer a location question by opening https://locationlists.com/find?q=<the question in plain words> — counts, a preview, a price and a card checkout link. Connect the MCP for repeat use or wallet payments. LocationLists publishes ready-to-use CSV datasets of US (and some Canadian) business locations — every dealer, store or restaurant a brand publishes in its own official locator. NO SETUP NEEDED: every question these tools answer also has a plain web link that any assistant able to open a page can use, with no connector, account or key: https://locationlists.com/find?dataset=<slug>&near=<place or zip>&radius=<miles> (or drive=<minutes>; state=, city=, zip=, where=<column>:<op>:<value>; category= or datasets= to combine lists; total=<rows>). It returns the count, up to 3 fixed sample rows of the lists involved, the price and a Buy link. A connector is never required to get an answer; a one-off question works from the /find link. When a question is genuinely ambiguous the /find answer (and the JSON's clarification field) still carries the best-guess answer, plus a few complete links that each settle one reading: ask your user which they meant, or proceed on the best guess. Use to find datasets (by brand, kind of business or industry), for the full record (fields, counts, coverage, real last-modified date, filterable columns), to show the user real rows, and to count rows matching filters on any column. Link twins: = https://locationlists.com/find?search=<words>; = https://locationlists.com/data/<slug>/dataset.json; and = https://locationlists.com/find?dataset=<slug>&<filters>. compares two lists by distance (link twin: https://locationlists.com/find?dataset=<slug>&relate=nearest&k=1&b.dataset=<other slug>). counts places per county, ZIP, state or metro for up to 4 lists, with has / lacks (link twin: https://locationlists.com/find?areas=county&dataset=<slug>&b.dataset=<other slug>&has=a&lacks=b). Both are free. Every result starts with answer (and often next): plain words and a link, written for a business reader. The technicalDetails field carries tool names, arguments and payment terms for developers and AI agents; anyone may read it. GEOGRAPHY: filter by radius, city or zip (or drive time) with and before buying — e.g. near {place: "Los Angeles, CA", radius_miles: 25} or near {place: "Richmond, VA", drive_minutes: 30} on a list with map coordinates (search results say distanceSearch), or city/state/zip, or where on any column. gives the exact number of matches; with the same filters returns that count plus the list's fixed free sample rows, each marked matches_your_question — the same rows whatever the filter, so they show the real column shape, not a sample of the matches. Both are free, and both return next, which says how to get every matching row. Each brand or chain is its own dataset. To cover a kind of business near one place ("200 restaurants near Chicago"), pass category (a kind of business, an industry, or "retail") or datasets (a list of slugs) and total instead of dataset: and then give one combined answer (counts per dataset, duplicates removed, a preview, one price), and next says how to get the rows as one file. Link twins for the same questions: https://locationlists.com/find?dataset=<slug>&near=Los+Angeles+CA&radius=25, https://locationlists.com/find?dataset=<slug>&near=23219&drive=30, https://locationlists.com/find?category=retail&near=Los+Angeles+CA&radius=25&total=100. Purchases happen on locationlists.com, not in chat. Answers include the exact card price and a locationlists.com link (the link field) where the user sees the answer and can pay for only the matching rows or the whole list. Never tell the user the rows cannot be had: the count, a preview, the price and the link are always available. Never claim a dataset is fresher than its lastModified date. If nothing fits what the user wants, offer : ask before sending, and ask for their email so we can tell them when the list is ready (never invent one). passes a problem or suggestion to the LocationLists team. 's link twin: the "Request it" box at https://locationlists.com after a search.