Food Near Me — MCP Server
MCP serverDev toolsYour AI can find restaurants nearby and answer questions about what they serve, including allergy-safety details that come signed. Restaurant information is organized into tiers, so your AI can tell verified listings apart from menu-indexed ones and general discoveries.
Use Food Near Me — MCP Server in Claude, ChatGPT or Ahel Desktop
Free. Sign in, add Food Near Me — MCP Server and connect your AI. About a minute.
Also: Claude Code · Cursor · Codex
Then ask your AI: use Food Near Me to search restaurants
No key or account is asked for. Not verified by us yet: Ahel has not run a call through it.
Details
Available today. Use it from your connected AI after setup.
No key or account is asked for. Not verified by us yet: Ahel has not run a call through it.
After adding it, ask your AI to find food near you or look up allergy details for a restaurant you have in mind. Setup and documentation are in the food-near-me platform repository on GitHub.
What your AI can do with it
- Find restaurants near you
- Look up menu details for a restaurant
- Check signed allergy-safety information before recommending a place
- Distinguish verified restaurants from menu-indexed and discovered results
Install Food Near Me — MCP Server
The server’s own address, for the clients that take one directly. Or connect Ahel once and every client you use reads it from one address, with the account kept on Ahel rather than in each client’s config.
Claude Code
claude mcp add --transport http --scope user food-near-me-mcp-server 'https://foodnear.me/mcp'Run it once in your project, then open /mcp to approve any sign-in the server asks for.
Claude Desktop
https://foodnear.me/mcpAdd a custom connector in Settings, paste this address, and approve the sign-in.
Cursor
cursor://anysphere.cursor-deeplink/mcp/install?name=food-near-me-mcp-server&config=eyJ1cmwiOiJodHRwczovL2Zvb2RuZWFyLm1lL21jcCJ9Open the link and Cursor adds the server at that address.
ChatGPT
https://foodnear.me/mcpIn Settings, enable Developer mode, create an MCP app, and paste this address. Your plan and workspace must allow custom apps.
Codex
codex mcp add food-near-me-mcp-server --url 'https://foodnear.me/mcp'Run it once, then sign in with codex mcp login food-near-me-mcp-server if the server asks for an account.
From the project's README
As published by food-near-me/platform in README.md.
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)
{
"mcpServers": {
"foodnear-me": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://foodnear.me/mcp"]
}
}
}
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)
| Tool | Description |
|---|---|
search_restaurants | Three-tier geo search by lat/lng — verified → menu_indexed → discovered; check menu_available before get_menu |
get_restaurant | Restaurant profile with Schema.org JSON-LD + Menu Protocol extensions |
get_menu | Full Menu Protocol v1.0 menu (dietary flags, allergens, signatures) |
get_ado_score_breakdown | ADO score factors and improvement recommendations |
validate_menu_protocol | Validate a Menu Protocol JSON payload before publish |
explore_area_for_diet | Composite: bucketed neighborhood overview (verified / menu_indexed / discovered); optional dietary filter narrows the verified tier only |
compare_restaurants_for_diet | Composite: compare 2–5 known restaurants by dietary-eligible menu items and trust tier ranking |
find_restaurants_along_route | Composite: route-adjacent restaurant discovery between origin/destination with optional dietary ranking |
Resources (4)
| URI | Content |
|---|---|
foodnearme://spec/menu-protocol | Menu Protocol v1.0 specification |
foodnearme://spec/openapi | OpenAPI 3.1 spec pointer |
foodnearme://agent/skill | Agent skill summary |
foodnearme://examples/search-flow | Example search → menu flow |
Prompts (3)
| Prompt | Args | Guides agent to |
|---|---|---|
find_dinner_near_me | location (required), cuisine?, dietary? | search_restaurants → get_menu |
dietary_constrained_menu | restaurant_id, restrictions | get_menu with explicit MP flags/allergens |
validate_my_menu | strict? (true for strict mode) | validate_menu_protocol |
Configuration
| Setting | Value |
|---|---|
| MCP URL | https://foodnear.me/mcp |
| Transport | HTTP JSON-RPC (POST); discovery via GET /mcp |
| Auth | None during beta (rate limits apply) |
| Registry | me.foodnear/foodnear-me (official MCP Registry) |
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
┌─────────────────────┐ POST /mcp (JSON-RPC) ┌─────────────────────────┐
│ MCP host │ ────────────────────────────▶│ apps/web/app/mcp │
│ (Cursor / Claude) │ GET /mcp (discovery) │ Next.js route handler │
└─────────────────────┘ └────────────┬────────────┘
│
▼
┌─────────────────────────┐
│ Supabase + PostGIS │
│ Menu Protocol (MP) │
└─────────────────────────┘
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:
| Field | Meaning |
|---|---|
code | VALIDATION_ERROR · NOT_FOUND · UPSTREAM · RATE_LIMITED · UNKNOWN |
message | What went wrong |
hint | How to fix the request |
retryable | Whether the agent should retry |
docs | https://foodnear.me/docs#quick-start |
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):
# Automated agent flows (14 flows when Supabase + seed configured; 11 without DB)
npm run test:mcp-flows
# Against production
npm run test:mcp-flows:http
# Discovery GETs + MCP tools/list count
npm run smoke:mcp
# Three-tier trust model copy parity (local files)
npm run check:discovery-copy
# Full deploy gate (13 checks + discovery copy on production URL)
npm run preflight -w web
# or: ./apps/web/scripts/deploy-preflight.sh https://foodnear.me
Production monitoring: GitHub Actions workflow MCP Production Smoke runs smoke:mcp daily and on manual dispatch (.github/workflows/mcp-smoke.yml).
Agent discovery
| File | URL |
|---|---|
llms.txt | https://foodnear.me/llms.txt |
llms-full.txt | https://foodnear.me/llms-full.txt |
| MCP manifest | https://foodnear.me/.well-known/mcp-server.json |
| AgentRoot | https://foodnear.me/.well-known/agentroot.json |
| Skill file | https://foodnear.me/SKILL.md |
| OpenAPI | https://foodnear.me/openapi.json |
| Web quick reference | https://foodnear.me/docs |
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:
| Path | Purpose |
|---|---|
apps/web | Next.js app — MCP at /mcp, landing, API routes |
packages/menu-protocol | Menu Protocol schema + validators |
database | Migrations, seeds, schema |
server.json | Official MCP Registry metadata |
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
npm install
cd apps/web && cp .env.example .env.local # Supabase keys
npm run dev # http://localhost:3000
npm run test:mcp-flows # POST localhost:3000/mcp
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.
cd apps/web
npm run db:probe:menu-batch -- --headless --limit=10
npm run db:import:menu-indexed:website:headless:dry-run -- --limit=10
npm run db:import:menu-indexed:website:headless -- --limit=10 # live
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 · api@foodnear.me
Tools it offers (9)
What this server listed when Ahel dialed its public endpoint in Oct 2026, with no key and no account of yours. The names are the server’s own.
search_restaurantsget_restaurantget_menuget_ado_score_breakdownget_safety_attestationvalidate_menu_protocolexplore_area_for_dietcompare_restaurants_for_dietfind_restaurants_along_route
Signals
- Last commit
- Sep 2026
Advanced
- Delivery
- foodnear-me MCP server → your Ahel connector (mcp.ahel.ai) → your AI.
- Item type
- mcp-server
- Key
me-foodnear-foodnear-me- Source
- github.com/food-near-me/platform
- Hosted endpoint
https://foodnear.me/mcp
github.com/food-near-me/platform