
Splitbasket Prices
io.github.voicearc由 GitHub 帳號 voicearc 發布v1.0.0更新於 Oct 24, 2026
Cached US grocery prices, age disclosed on every row - search, compare across banners, coverage.
概覽
遠端 MCP 伺服器,提供美國雜貨快取價格:依地點搜尋商品、跨通路比價並查詢涵蓋範圍。
- 可以做什麼
- 依地點搜尋附近商品,並列出各門市最近一次顯示的價格
- 查詢某個地點某一特定商品的快取價格
- 針對一個查詢在各通路品牌間比較最佳匹配,依標準單位價格排序
- 在提問前先確認該地點能回答哪些問題
- 發起付費的零售商即時抓取並輪詢任務狀態
- 適用情境
- 當助理需要某個郵遞區號或都會區的美國雜貨價格資料時適用,例如比較各通路的民生必需品價格,或逐項估算購物清單。在不熟悉的地區應先查詢涵蓋範圍,因為各地資料深度不同。
- 執行需求
- 遠端 Streamable HTTP 端點,使用 bearer 驗證,需在 Authorization 標頭中帶入 API 金鑰。金鑰免費,但處於封閉測試階段、由人工核發,需以電子郵件申請。需要網路連線。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Splitbasket Prices,將其新增到工作區。
- 連接 Authorization token 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
- 為需要使用其工具的對話啟用該服務。
Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。
交給代理程式安裝
把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。
閱讀 https://sourceweft.com/mcp/io.github.voicearc%2Fsplitbasket-prices/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。其他 MCP 客戶端
把它新增到你客戶端的 mcpServers 設定中。
{
"mcpServers": {
"splitbasket-prices": {
"type": "http",
"url": "https://api.splitbasket.shop/v1/mcp",
"headers": {
"Authorization": "Bearer <YOUR_TOKEN>"
}
}
}
}README
SplitBasket Grocery Prices — MCP server & data API
Cached US grocery prices for developers and agents, from the price panel behind
SplitBasket. Every price carries its observation
date; the API tells you what it can answer at a location before you ask, and
returns found: false rather than a plausible wrong number.
- API docs & quickstart: https://splitbasket.shop/developers
- Terms: https://splitbasket.shop/api-terms
- Get a key (free, closed beta): email [email protected] — one line about what you're building; keys are issued by a human, usually within a day.
Connect over MCP
Endpoint: https://api.splitbasket.shop/v1/mcp (Streamable HTTP, bearer auth)
Claude Code:
Any MCP client that speaks Streamable HTTP works the same way — point it at the
endpoint with the Authorization header.
Or plain HTTP
Tools
Coverage, honestly
Two layers (measured weekly — 2026-08-09; coverage is the runtime source of truth):
- National layer — six banners: Walmart, Costco, Whole Foods, Sprouts, Sam's Club, Aldi. 51 states (incl. DC) with at least one priced, 2+ banner comparison in 50, 3+ in 46 (measured 2026-08-11). These stores are priced weekly against a ~43-item staples basket.
- Deep metros — San Francisco, Fresno, Phoenix, Austin: 7–17 banners with full shopping catalogs.
Prices are cached observations, not live quotes. Exact-match rate by cache age,
measured over 275k observation pairs: 99.6% under a day, 93.8% at a week, 79.9%
at 30 days. Every row carries price_as_of and price_age_days; pass
max_age_days to enforce what your use case tolerates.
What this deliberately is not
- No basket optimizer. To estimate a basket, call
compare_priceper item and sum it yourself. - No state-level answers where prices measurably don't hold state-wide. Chain-wide for target, smartandfinal, bashas, frys, foodsco — and per-state where a chain is bimodal: Costco in ten measured states, Whole Foods in CA and NV. Measured, not assumed; the demote list tracks the weekly panel.
- No blended accuracy score. Price staleness is bimodal: a stale price is either exactly right or meaningfully wrong, so we disclose age instead of averaging it away.
Operated by VoiceArc Inc. Not affiliated with or endorsed by any retailer; retailer names identify where a price was observed.
來源:README.md,提交 7d6d4f1
工具
0版本歷史
1- v1.0.0最新Sep 16, 2026
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