Spree Commerce developer docs for AI agents
Spree Commerce docs for AI coding agents: build headless B2B and marketplace ecommerce on its APIs.
作者による説明(英語の原文)
US business location data: search, sample, count, query rows or buy CSVs (Stripe or x402 USDC).
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
ウェブ、デスクトップ、モバイルのClaudeで使えます:
https://locationlists.com/mcpターミナルでこれを実行します
claude mcp add --transport http locationlists https://locationlists.com/mcpプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"locationlists": {
"url": "https://locationlists.com/mcp"
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"locationlists": {
"type": "http",
"url": "https://locationlists.com/mcp"
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
ChatGPTがつなげるのは、インターネット上のサーバーだけです:
https://locationlists.com/mcpメニューの名前は、プランや時期によって少し違うことがあります。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
このサーバーのつなぎ方と、各アプリの公式ドキュメントに基づきます。2026年11月10日に確認。
インターネット経由でつなげるアプリ
ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast
ツールの名前と説明は、サーバーが2026年11月9日に返したそのままの内容です。書いたのは作者で、私たちではありません。プレーンテキストとして表示しています。
search_datasetsFind 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
relate_locationsFree. 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 (ran
count_by_areaFree, 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 ha
cotenancyFree, 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 d
get_datasetFull 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, ad
count_locationsFree. 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 mista
get_sampleFree. 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`
request_listAsk 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 w
send_feedbackSend 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;
email_quoteFree. 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:
get_quoteLine-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
create_checkoutOpens 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.
check_orderGiven 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
create_query_checkoutFor 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`) a
query_locationsReturn 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, K
buy_datasetBuy 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 que
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月10日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント kylehawke-stack で確認済みです
コードの最終更新:2 か月前
このリポジトリはまだGitHubから読み取っていません
230ミリ秒で応答(HTTP 200)
サインイン不要
16件のツールの説明を読み、AIへの隠れた指示は見つかりませんでした
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック4項目のうち4項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
作者のクラウドで動きます。インストール不要でインターネット経由でつながりますが、送った内容は作者のサーバーを通ります。
GitHubリポジトリの最終更新は2 か月前、最新バージョン(1.2.0)がレジストリに届いたのは2 か月前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。URLでつながるので、リモートMCPサーバーに対応したアプリ(開発者モードのChatGPTなど)でも使えます。
同じカテゴリには:Spree Commerce developer docs for AI agents, Spree Commerce: open-source B2B and marketplace ecommerce, Stripe MCP
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:↓ 週あたりのダウンロードi★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
Spree Commerce docs for AI coding agents: build headless B2B and marketplace ecommerce on its APIs.
Open-source B2B and marketplace ecommerce; new stores include an MCP server for AI agents.
MCP server integrating with Stripe - tools for customers, products, payments, and more.
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
No connector needed: any AI assistant can answer a location question by opening https://locationlists.com/find?q= — counts, a preview, a price and a card checkout link. Connect the MCP for repeat use or wallet payments.
Open the link. No account, no key, no setup. The answer comes back with how many locations match, a few real rows, the price and a checkout link.
Or set no parameters at all and put the question itself in q=, in plain words.
Everything below is for repeat use and wallet payments.
Listed on Smithery · Glama · Official MCP Registry · x402scan
Business location data for AI agents. Search, sample, count and buy ready-to-use lists of US business locations: 966 datasets compiled from each brand's official store locator or the public register that publishes the data.
Filter by city, state, zip, a radius around any place, or any column in the file. Buy a full CSV by card, or let an agent pay per row or buy the whole file in USDC on Base via x402, with no account or API key. A failed or empty query costs nothing.
This repository holds the registry listing (server.json) and client setup notes for the hosted LocationLists MCP server. The server runs at locationlists.com; there is nothing to install or run locally.
| Endpoint | https://locationlists.com/mcp |
| Transport | Streamable HTTP, stateless, JSON responses |
| Auth | None |
| Payments | Stripe Checkout (people) or x402, USDC on Base (agents) |
| Registry name | io.github.kylehawke-stack/locationlists |
| Read-only profile | https://locationlists.com/mcp/chatgpt (search, dataset, sample, count only; no checkout) |
Figures are read from the live catalog.json (generated 2026-09-16):
All nine tools are on /mcp. Tools carry readOnlyHint / destructiveHint / openWorldHint annotations. initialize returns serverInfo.name = "LocationLists".
Free tools:
| Tool | Arguments | What it does |
|---|---|---|
search_datasets | query? string, category? enum, limit? int (≤50) | Find datasets by brand, product line, location type or category. Returns slug, name, record count, coverage and page URL. |
get_dataset | slug string | Full record: fields with descriptions, record and state counts, coverage, refresh cadence, the real last-modified date of the file, FAQs, sample URL and page URL. |
get_sample | slug string, rows? int (≤10) | Up to 10 real rows from the live file, spread across the dataset, as JSON plus CSV text. |
count_locations | dataset string, state?, city?, county?, zip?, where? array | How many rows match a filter on geography and any other column (e.g. revenue_amt gt 2000000), and what fetching them would cost. |
get_quote | slugs string[] | Line-item prices and total for one or more datasets; points out a bundle if it covers several requested brands for less. |
Card checkout (Stripe):
| Tool | Arguments | What it does |
|---|---|---|
create_checkout | slug string, email? string | Opens a Stripe Checkout session for one dataset and returns the payment URL and session id. Does not charge anything by itself. |
check_order | sessionId string | Reports whether a Checkout session is paid and, if so, returns the permanent download link. |
Agent payments (x402, USDC on Base):
| Tool | Arguments | What it does |
|---|---|---|
query_locations | dataset string, state?, city?, county?, zip?, where? array, order_by? object, offset? int, limit? int (≤100) | Rows from one dataset filtered on any column, sorted and paged. Priced per row and settled only after the rows are produced. Datasets under 5,000 records are not sold by the row. |
buy_dataset | dataset string | Buy a whole dataset outright and get a permanent download link for the CSV, at the same list price a card buyer pays. |
query_locations and buy_dataset use x402, the HTTP 402 payment protocol. An agent that holds USDC on Base can buy data with no account, API key or checkout page:
query_locations) or the permanent download link (buy_dataset). Per-row queries settle only after the rows are produced, so a failed query costs nothing.Pricing rules the agent can rely on:
count_locations is free and reports how many rows a filter matches and what they would cost, before any payment.limit you request.buy_dataset is cheaper than assembling the file row by row, and it is complete.Clients without a wallet can use get_quote → create_checkout → check_order and pay by card instead.
claude mcp add --transport http locationlists https://locationlists.com/mcp
~/.cursor/mcp.json){
"mcpServers": { "locationlists": { "url": "https://locationlists.com/mcp" } } }
.vscode/mcp.json){
"servers": { "locationlists": { "type": "http", "url": "https://locationlists.com/mcp" } } }
https://locationlists.com/mcp, no OAuth.https://locationlists.com/mcp/chatgpt, no auth. The read-only profile is used there because in-chat purchase of digital goods is not permitted in ChatGPT.curl -s https://locationlists.com/mcp \
-H 'Content-Type: application/json' \ -H 'Accept: application/json, text/event-stream' \ -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"search_datasets","arguments":{"query":"bobcat"}}}'
A quick path through the tools: search_datasets {query:"bobcat"} → get_sample {slug:"bobcat-dealers"} → count_locations {dataset:"bobcat-dealers", state:"TX"} → get_quote {slugs:["bobcat-dealers"]} → create_checkout {slug:"bobcat-dealers"} → check_order {sessionId}.
| URL | What |
|---|---|
/llms.txt | Curated map of the site for assistants (llmstxt.org) |
/llms-full.txt | Every dataset with fields, counts, refresh and price |
/catalog.json | The same catalog as JSON |
/data/{slug}/dataset.json | One dataset in full, including the real last-modified date |
/data/{slug}/sample.csv, /data/{slug}/sample.json | 10 real rows, no signup |
/data/{slug}/buy?src= | Redirects to Stripe Checkout for that dataset |
Example: bobcat-dealers/dataset.json, bobcat-dealers/sample.csv.
The files in this repository (README, server.json) are MIT licensed; see LICENSE. The datasets sold through the server are not covered by that license; they are governed by https://locationlists.com/license.