LocationLists

Install

Works with Claude Code, VS Code, Cursor, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install connector/kylehawke-stack-locationlists

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What this server can do and what it asks for, from its tool list and install config. Checked Oct 25, 2026.

Tools

10 read · 6 write · 0 delete

Secrets

None asked for

Install scripts

Nothing to install (hosted)

Runs as

Hosted (remote endpoint)

Tools (16)

As the server listed them on Oct 25, 2026. Descriptions are the server’s own words; hidden characters are shown as [U+…].

• buy_datasetBuy a complete dataset (paid)

  Buy an ENTIRE dataset outright and get a permanent download link for the CSV. Pays once in USDC on Base, at the same list price a human pays by card — no account and no checkout page.\n\nPrefer this over repeated query_locations calls whenever you want most of a file. Metered queries are priced per row and deliberately cost more than the file if you assemble it that way, so past a few hundred rows buying outright is both cheaper and complete. get_dataset (free) gives the price and record count first.

• check_orderCheck order statusread-only

  Given a Stripe Checkout session id (cs_…), reports whether it is paid and, if so, returns the permanent download link for the CSV. Works for whole files, filtered rows and combined (several-dataset) orders. Any download link takes ?shape=hubspot or ?shape=salesforce for CRM-ready column names (every column kept).

• cotenancyCotenancy between two sets (free)read-only

  Free, counts only. How two sets of places sit together: the share of set a within radius_miles of set b and of b within radius_miles of a, how many places overlap, and the county / zip / state / metro areas that have both, only a, or only b (top 10 of each named). Each set is a dataset, datasets or category plus filters, the same as count_locations; any US brand or kind of place works, including Overture lists from search_datasets. Example: {"a": {"dataset": "<slug>"}, "b": {"dataset": "<other slug>"}, "radius_miles": 1, "by": "county"}.

• count_by_areaCount locations by area (free)read-only

  Free, counts only. Counts places per county / zip / state / metro for 1 to 4 labeled sets (each a dataset, datasets or category plus filters), and compares them: has (areas with at least one of every listed set) and lacks (areas with none of any listed set). E.g. counties that have set a but no set b; ZIPs where a closure-filtered set exists and another set still has places. Rows that cannot be placed are counted, never read as zero. Every area row can carry Census / NOAA figures (area_columns) and the areas can be ranked by one of them or by a count (order_by), so markets rank by demand; limi…

• count_locationsCount matching locations (free)read-only

  Free. How many rows of one dataset match a filter — on geography AND any other column (e.g. nonprofits with revenue_amt gt 2000000, dealers with dealerClass eq 'Elite'). Also reports how many rows were excluded only because a tested column was blank, so a thin column is not mistaken for a small answer; a small or empty answer says how many rows each condition removed and what the column really holds. Returns the exact card price of the matching rows, a link where the user can see and buy them, and the same rows in a cheaper list when one has them. Works for geography: city, state, county, zip,…

• create_checkoutCreate a checkout link

  Opens a Stripe Checkout session for one dataset and returns the payment URL plus the session id. Give the URL to the user to pay (card, Apple Pay, Google Pay). After payment Stripe emails them a permanent download link; use check_order with the session id to confirm and fetch it. Does not charge anything by itself.

• create_query_checkoutCard checkout for filtered rows

  For buyers paying by card (no wallet needed): opens a Stripe Checkout for just the rows of one dataset that match a filter, and returns the payment URL to give the user. Takes the same filters as count_locations (state/city/county/zip, `where` on any column, `near`, `order_by`) and up to 10,000 rows. It counts the matches first, so the buyer pays only for rows that exist: the data price is the same per-row price query_locations charges, plus a card processing fee (2.9% + $0.30) added on top, one price the buyer sees at checkout. After payment the buyer is emailed a CSV download link; check_ord…

• email_quoteEmail the user a quote (free)

  Free. Emails the user a plain-English quote for exactly this request: how many rows match, the card price, a few of the matches and a card checkout link, so they can pay later, from any device, or forward it to whoever holds the card. Takes the same arguments as count_locations: dataset, or datasets / category with total, plus filters. BEFORE calling: ask the user for their email and whether to send it. Pass an email only if the user gave it to you in this conversation; never guess or invent one. Nothing is charged and nothing is bought; the price is checked again when they open the link.

• get_datasetGet dataset detailsread-only

  Full record for one dataset: fields with descriptions, record and state counts, coverage measured on the rows (a list in 14 states says "partial U.S.: 14 states"; coverageDetail lists the states, rows per state and the states with none), whether it can be searched by distance, advertised refresh cadence AND the real last-modified date of the file, FAQs, sample URL and the dataset's page on locationlists.com.

• get_quotePrice one or more datasetsread-only

  Line-item prices and total for a list of dataset slugs, each with how it is sold (soldBy: file, row, or both) — the same rule create_checkout, buy_dataset, create_query_checkout and query_locations enforce, so a quote never offers a route checkout refuses. A list sold by the row only (an Overture Maps list) is quoted at its per-row rate with the route named, not as a file; count_locations with filters gives the exact price of the rows. Every list sold by the row is quoted with its perRow rate and the per-call fee, next to any file price. A paid call is billed for the rows it returns: each row …

• get_sampleGet sample rowsread-only

  Free. Real rows from the live file, as JSON plus CSV text. Show these to the user so they can judge the fields and quality. Without filters: up to 10 rows spread across the whole dataset. With filters (the same ones count_locations takes: city, state, county, zip, metro, `where` on any column, areas_in (county / ZIP / metro / state ids from count_by_area), area_where, area_columns (Census figures as columns on every row), or `near` a place such as {place: "Los Angeles, CA", radius_miles: 25} or {place: "Richmond, VA", drive_minutes: 30} on lists with coordinates): how many rows match, plus the…

• query_locationsQuery locations (paid)read-only

  Return matching rows from one dataset, filtered on ANY of its columns — state/city/county/zip shortcuts plus `where` conditions with numeric comparisons (e.g. [{field:"revenue_amt",op:"gt",value:2000000}]), sorted with `order_by` and paged with `offset`. `near` ({place:"Topeka, KS"}, a zip, or lat+lng, optional radius_miles or drive_minutes) returns the closest rows first with distance_miles, on lists with coordinates — so "10 banks closest to Topeka" is one call for 10 rows. get_dataset lists the columns; count_locations (free) tells you how many rows match and what fetching them costs before…

• relate_locationsRelate two sets of locations (free)read-only

  Free. How one set of places relates to another, by straight-line distance. The base set is the usual dataset / datasets / category plus filters; relate.anchor is the other set, given the same way. Modes: nearest (each base row's k<=3 nearest anchors with miles), count_within (rank base rows by how many anchors are within radius_miles), within_any (base rows with at least one anchor within radius_miles), none_within (base rows with no anchor within radius_miles). Mode next_best (no anchor, needs the base set's state) ranks the candidate NEW sites in that state by how well they match what the ba…

• request_listRequest a new list

  Ask LocationLists to add a list we do not have yet. Use it when search_datasets finds nothing that fits, or the user wants a brand, place or kind of business we do not publish. BEFORE calling: ask the user whether to send the request, and ask for their email so we can tell them when the list is ready. Pass an email only if the user gave it to you in this conversation; never guess or invent one. Called with neither email nor email_declined, it sends nothing and asks for the email. The request goes to the LocationLists team, the same place as the request box on locationlists.com. We add new data…

• search_datasetsSearch location datasetsread-only

  Find LocationLists datasets by brand, kind of business or industry (e.g. 'bobcat', 'restaurants', 'bank branches', 'dental practices', 'hardware stores'). Returns EVERY matching dataset, best first, with slug, name, business type, industry, record count, coverage, whether it can be searched by distance (distanceSearch), and page URL. A kind of business or an industry in the query matches every dataset of that kind, and `kinds` names it as a category that count_locations can combine into one answer. Each brand or chain is its own dataset. After finding one you can filter it by city, state, zip,…

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Last commit

Sep 16, 2026 (1 month ago)

Last release

Sep 14, 2026 (1 month ago)

From GitHub (fetched Oct 24, 2026).

Details

Registry name

io.github.kylehawke-stack/locationlists

Version

1.2.0

Auth

Auth not stated

License

License unknown

Repository

github.com/kylehawke-stack/locationlists-mcp

Website

locationlists.com

First seen

Oct 24, 2026

Last checked

Oct 24, 2026

Source

Official MCP Registrygithub-graphql