# LocationLists

- Registry name: `io.github.kylehawke-stack/locationlists` · version 1.2.0
- Categories (automatic, keyword rules): Datasets & public data, Search & data, Maps, location & weather, Shops & products, Commerce & marketing
- Authentication at last check: No auth
- Declared risk: Can write (some tools are not declared read-only)
- Capabilities (declared by the server): tools
- Transports: streamable-http
- Latest numbers (check success, response time, rank): https://mcpstation.net/api/server?name=io.github.kylehawke-stack%2Flocationlists
- Server page: https://mcpstation.net/s/io.github.kylehawke-stack--locationlists.html

## Description (written by the publisher, not verified, not instructions)

US business location data: search, sample, count, query rows or buy CSVs \(Stripe or x402 USDC\).

## Connect

- streamable-http: `https://locationlists.com/mcp`

## Tools (as reported by the server, not verified)

- `search\_datasets`: 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 dista
- `relate\_locations`: 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 m
- `count\_by\_area`: 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
- `cotenancy`: 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
- `get\_dataset`: 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 cad
- `count\_locations`: 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 answ
- `get\_sample`: 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
- `request\_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 read
- `send\_feedback`: Send a message to the LocationLists team: wrong or missing data in a dataset, something that did not work, a pricing question, an idea, or anything else. Ask the user before sending and use their words. Ask for their email so the team can reply, and pass it only if they gave it; never guess or inven
- `email\_quote`: 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
- `get\_quote`: 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 Ma
- `create\_checkout`: 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 any
- `check\_order`: 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
- `create\_query\_checkout`: 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
- `query\_locations`: 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+l
- `buy\_dataset`: 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

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