
Food Near Me
me.foodnearPublished by foodnear.meOfficial publisherv1.1.0Updated Nov 2, 2026
AI-native restaurant discovery: verified/menu-indexed/discovered tiers + signed allergy-safety data.
Overview
Remote MCP server for AI-native restaurant discovery: geo search across trust tiers, Menu Protocol menus, dietary comparison and signed allergy-safety data.
- What you can do
- Search restaurants by coordinates across verified, menu-indexed and discovered tiers, and read a restaurant profile.
- Fetch full Menu Protocol menus with dietary flags and allergens, and validate a menu payload before publishing.
- Explore a neighborhood for a diet, compare two to five restaurants by dietary-eligible items, and find places along a route.
- Retrieve signed allergy-safety attestations and a short curated list of safe places for an allergy need.
- Read bundled resources (Menu Protocol spec, OpenAPI pointer, agent skill, example flow) and use three guided prompts.
- When to use it
- Useful when an assistant should recommend places to eat near a location, filter by cuisine or dietary needs, show menus, or answer allergy-safety questions with explicit trust tiers. Best suited to hosts that can reach a remote HTTP MCP endpoint.
- Requirements
- A remote MCP endpoint at foodnear.me/mcp over HTTP JSON-RPC; the README suggests bridging it with npx mcp-remote for hosts such as Cursor or Claude Desktop, which needs Node.js. No API key during beta, but rate limits apply. Coverage is concentrated in seeded US metros.
Installation
In SourceWeft
- Open Food Near Me in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.
Use with an agent
Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.
Read https://sourceweft.com/mcp/me.foodnear%2Ffoodnear-me/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.Other MCP clients
Add this to your client's mcpServers config.
{
"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]
Source: README.md at commit 7c5156a
Tools
0Version history
1- v1.1.0LatestSep 16, 2026
Score
75% of the applicable checks met
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