
Food Near Me
me.foodnear由 foodnear.me 發布官方發布者v1.1.0更新於 Nov 2, 2026
AI-native restaurant discovery: verified/menu-indexed/discovered tiers + signed allergy-safety data.
概覽
面向 AI 的餐廳探索遠端 MCP 伺服器:依信任層級的地理搜尋、Menu Protocol 菜單、飲食比較與簽章的過敏安全資料。
- 可以做什麼
- 依座標搜尋餐廳,結果分為已驗證、菜單已索引、僅探索三個層級,並檢視餐廳資料。
- 取得完整的 Menu Protocol 菜單(含飲食標記與過敏原),並在發布前驗證菜單資料。
- 依飲食需求探索街區、比較 2 至 5 家餐廳的可用餐點,並尋找路線沿途的餐廳。
- 取得簽章的過敏安全聲明,以及針對某種過敏需求最多 3 家人工精選場所。
- 讀取內建資源(Menu Protocol 規格、OpenAPI 指標、代理技能、範例流程),並使用三個引導提示。
- 適用情境
- 適合讓助理推薦附近餐廳、依料理或飲食需求篩選、顯示菜單,或依明確的信任層級回答過敏安全問題。較適合能連線遠端 HTTP MCP 端點的宿主。
- 執行需求
- 需要可連線的遠端 MCP 端點 foodnear.me/mcp(HTTP JSON-RPC);README 建議以 npx mcp-remote 橋接給 Cursor、Claude Desktop 等宿主,這需要 Node.js。測試期間不需 API 金鑰,但有速率限制。資料涵蓋範圍集中在已預先匯入的美國都會區。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Food Near Me,將其新增到工作區。
- 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/me.foodnear%2Ffoodnear-me/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": {
"food-near-me": {
"type": "http",
"url": "https://foodnear.me/mcp"
}
}
}README
Food Near Me — MCP Server
Model Context Protocol server for AI-native restaurant discovery — three-tier search (verified → menu_indexed → discovered), Menu Protocol menus, and structured menu validation. Plug into Claude Desktop, Cursor, ChatGPT, or any MCP host in about 30 seconds.
Production endpoint: https://foodnear.me/mcp · 8 tools · 4 resources · 3 prompts · No API key (beta)
Quick start {#quick-start}
1. Add this to your MCP host config
Cursor — ~/.cursor/mcp.json (macOS/Linux) or %USERPROFILE%\.cursor\mcp.json (Windows)
Claude Desktop — ~/Library/Application Support/Claude/claude_desktop_config.json (macOS), %APPDATA%\Claude\claude_desktop_config.json (Windows)
2. Restart your MCP host
3. Try a prompt
“Find vegan Thai restaurants near Brooklyn Bridge and show me a menu for the top result.”
Your agent should call search_restaurants → get_menu (or get_restaurant first).
What you get
Tools (8)
Resources (4)
Prompts (3)
Configuration
Preview / local: Replace the URL with http://localhost:3000/mcp when running npm run dev in apps/web.
Operational tool filter: set FNM_MCP_ENABLED_TOOLS=search_restaurants,get_menu to expose only a comma-separated subset in tools/list and GET /mcp. Leave unset or * to expose all tools. This is for temporary degradation/context control, not privacy or auth.
Architecture
Implementation: apps/web/app/mcp/route.ts · Flow runner: apps/web/lib/mcp/mcp-flow-runner.ts
Tool error contract
Failed tools/call responses include structured metadata in _meta.error:
Human-readable text is still in content[0].text for hosts that ignore _meta.
Verify
From repo root (with apps/web dev server running for localhost):
Production monitoring: GitHub Actions workflow MCP Production Smoke runs smoke:mcp daily and on manual dispatch (.github/workflows/mcp-smoke.yml).
Agent discovery
Scripted flows: apps/web/docs/example-agent-flows.md
Data trust model (three-tier search)
search_restaurantsreturns verified → menu_indexed → discovered.- Every result includes
verification_statusandmenu_available. Callget_menuonly whenmenu_availableis true. - Verified — owner-approved MP; authoritative for dietary/allergen claims.
- menu_indexed — automated/public MP menu; cite with caveat — not owner-verified.
- discovered — place only; do not cite menu items.
- Trust progression:
discovered→menu_indexed→verified. See https://foodnear.me/attribution for data sources.
FAQ
Do I need an API key?
No for beta MCP access. Future paid tiers may use API keys or x402 (USDC on Base). See x402-prepaid-spec.md in your local docs/Food Near Me playbook.
Tools not showing after restart?
Confirm the config URL ends with /mcp. Restart the host completely. Run npm run smoke:mcp against your target base URL.
Empty search results?
Beta verified menus are seeded for specific metros (e.g. Williamsburg, NYC). 7 menu_indexed restaurants in Williamsburg have automated menus from website ingest. Discovered place listings cover many US metros — use coordinates in an imported region. Demo coords: 40.7128, -74.006. Run npm run db:seed -w web locally for verified test data.
Cursor vs Claude config path?
See Quick start above — each host uses a different JSON file; only the mcpServers block matters.
How is this different from DoorDash / Uber Eats APIs?
We expose owner-verified Menu Protocol data for agents — not scraped aggregator menus or ordering checkout.
Monorepo layout
This repository ships the MCP server inside the foodnear.me web app:
Business strategy and runbooks live in a separate local docs folder (not in this repo) — see your team's docs/Food Near Me playbook.
Development
Operator: menu_indexed website ingest
Promote discovered → menu_indexed via free website/ordering-platform parsers (ChowNow API, order.online, Sauce, Squarespace, BentoBox, Toast, Playwright). Always dry-run first — headless is slow.
No Uber Eats / DoorDash / Grubhub / RapidAPI scrapers. See apps/web/docs/example-agent-flows.md.
Links
- Website: https://foodnear.me
- GitHub: https://github.com/food-near-me/platform
- Menu Protocol spec: https://github.com/foodnearme/menu-protocol
- Support: https://foodnear.me/support · [email protected]
來源:README.md,提交 7c5156a
工具
0版本歷史
1- v1.1.0最新Sep 16, 2026
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