Food Near Me

Official registry Maps, travel and weather

AI-native restaurant discovery: verified/menu-indexed/discovered tiers + signed allergy-safety data.

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

Remote (streamable-http)
Claude Code
claude mcp add --transport http food-near-me 'https://foodnear.me/mcp'
JSON configuration (Claude Desktop, Cursor, VS Code)
{
    "mcpServers": {
        "food-near-me": {
            "type": "http",
            "url": "https://foodnear.me/mcp"
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. Food Near Me — MCP Server
  2. Quick start {#quick-start}
  3. What you get
  4. Configuration
  5. Architecture
  6. Tool error contract
  7. Verify
  8. Agent discovery
  9. Data trust model (three-tier search)
  10. FAQ
  11. Monorepo layout
  12. Development
  13. Links

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)

{
  "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)
ToolDescription
search_restaurantsThree-tier geo search by lat/lng — verified → menu_indexed → discovered; check menu_available before get_menu
get_restaurantRestaurant profile with Schema.org JSON-LD + Menu Protocol extensions
get_menuFull Menu Protocol v1.0 menu (dietary flags, allergens, signatures)
get_ado_score_breakdownADO score factors and improvement recommendations
validate_menu_protocolValidate a Menu Protocol JSON payload before publish
explore_area_for_dietComposite: bucketed neighborhood overview (verified / menu_indexed / discovered); optional dietary filter narrows the verified tier only
compare_restaurants_for_dietComposite: compare 2–5 known restaurants by dietary-eligible menu items and trust tier ranking
find_restaurants_along_routeComposite: route-adjacent restaurant discovery between origin/destination with optional dietary ranking
Resources (4)
URIContent
foodnearme://spec/menu-protocolMenu Protocol v1.0 specification
foodnearme://spec/openapiOpenAPI 3.1 spec pointer
foodnearme://agent/skillAgent skill summary
foodnearme://examples/search-flowExample search → menu flow
Prompts (3)
PromptArgsGuides agent to
find_dinner_near_melocation (required), cuisine?, dietary?search_restaurants → get_menu
dietary_constrained_menurestaurant_id, restrictionsget_menu with explicit MP flags/allergens
validate_my_menustrict? (true for strict mode)validate_menu_protocol

Configuration

SettingValue
MCP URLhttps://foodnear.me/mcp
TransportHTTP JSON-RPC (POST); discovery via GET /mcp
AuthNone during beta (rate limits apply)
Registryme.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:

FieldMeaning
codeVALIDATION_ERROR · NOT_FOUND · UPSTREAM · RATE_LIMITED · UNKNOWN
messageWhat went wrong
hintHow to fix the request
retryableWhether the agent should retry
docshttps://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

Scripted flows: apps/web/docs/example-agent-flows.md


  • search_restaurants returns verified → menu_indexed → discovered.
  • Every result includes verification_status and menu_available. Call get_menu only when menu_available is 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:

PathPurpose
apps/webNext.js app — MCP at /mcp, landing, API routes
packages/menu-protocolMenu Protocol schema + validators
databaseMigrations, seeds, schema
server.jsonOfficial 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.


Frequently asked questions

What is Food Near Me?

AI-native restaurant discovery: verified/menu-indexed/discovered tiers + signed allergy-safety data.

How do I install Food Near Me?

It runs as a remote server. In Claude Code: claude mcp add --transport http food-near-me 'https://foodnear.me/mcp'. For other clients, paste the JSON configuration from this page into their MCP settings.

Does Food Near Me need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is Food Near Me open source?

Its code is public on GitHub, but the repository does not declare a standard license.

Who maintains Food Near Me?

It is published by food-near-me. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.