CAT
/MCP
SkillsMCPMarketplacesDigestToolsAdvertise

This week in Claude

Every Monday: Claude Code, Agent SDK, MCP, and the Anthropic platform moves worth your time.

Skills by Category
Frontend DevelopmentBackend & APIsTesting & QASecurityDevOps & CI/CDGit & Pull RequestsDocumentationCode Review & QualityAI & Agent BuildingSkill Development
MCP Servers by Category
Sales & MarketingWeb & Browser AutomationDatabasesAI & LLM ToolsCloud & InfrastructureCommunication & MessagingDeveloper ToolsDesign & CreativeDocuments & KnowledgeSearch & Web Crawling
Marketplaces by Category
AI Agents & OrchestrationLLM IntegrationDevelopment ToolsFrontend & UIBackend & APIsDatabasesTesting & Code QualityDevOps & CloudSecurity & ComplianceGit & Version Control

Cross AI Tools

Discover Claude Code plugins, extensions, and tools. Automatically updated directory of Anthropic Claude AI marketplaces with development tools, productivity plugins, and integrations.

Resources

  • Browse Skills
  • Browse MCP Servers
  • Browse Marketplaces
  • Plugins Reference

Community

  • About
  • Tools
  • Feedback
  • Privacy Policy
  • Advertise

Built for the Claude Code community with Claude Code by @mertduzgun

Independent project, not affiliated with Anthropic

Food Near Me

food-near-me/platform
HTTPregistry active
Summary

Gives your AI agent eight restaurant discovery tools backed by Menu Protocol validated menus. The three-tier search returns verified, menu_indexed, and discovered restaurants with structured dietary flags and allergen data. You get geographic search by lat/lng, full menu retrieval with dietary filtering, ADO score breakdowns, and composite tools for route-based discovery and restaurant comparison. Ships with resources for the Menu Protocol spec and three prompts that guide common flows. No API key during beta. Drop the npx command into Claude Desktop or Cursor's MCP config and you're querying Supabase-backed restaurant data with PostGIS search in under a minute. Useful when you need structured, citation-ready menu data instead of scraping review sites.

CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
Keep your Mac awake
Keep your Mac awake
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →
Context.devContext.dev
Context.dev
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
AppSignal
Monitor with ease. Code with confidence.
Start Free Trial →
CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
Keep your Mac awake
Keep your Mac awake
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →
Context.devContext.dev
Context.dev
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
AppSignal
Monitor with ease. Code with confidence.
Start Free Trial →

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.

MCP Registry

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

FileURL
llms.txthttps://foodnear.me/llms.txt
llms-full.txthttps://foodnear.me/llms-full.txt
MCP manifesthttps://foodnear.me/.well-known/mcp-server.json
AgentRoothttps://foodnear.me/.well-known/agentroot.json
Skill filehttps://foodnear.me/SKILL.md
OpenAPIhttps://foodnear.me/openapi.json
Web quick referencehttps://foodnear.me/docs

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


Data trust model (three-tier search)

  • 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.


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
Featured
CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
Keep your Mac awake
Keep your Mac awake
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →
Context.devContext.dev
Context.dev
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
AppSignal
Monitor with ease. Code with confidence.
Start Free Trial →
Categories
Data & Analytics
Registryactive
TransportHTTP
UpdatedMay 19, 2026
View on GitHub

Related Data & Analytics MCP Servers

View all →
Google Sheets

com.mcparmory/google-sheets

Create, read, and modify spreadsheet data, formatting, and sheets
25
Google Sheets

domdomegg/google-sheets-mcp

Allow AI systems to read, write, and query spreadsheet data via Google Sheets.
2
Google Sheets Mcp

henilcalagiya/google-sheets-mcp

Powerful tools for automating Google Sheets using Model Context Protocol (MCP)
14
Futuristic Risk Intelligence

cct15/war-dashboard-data

Geopolitical conflict risk, political events, and maritime traffic data for AI agents
1
Mcp Google Sheets Full

moooonad/mcp-google-sheets-full

Full Google Sheets MCP: 26 tools + run_sheets_script escape hatch. User OAuth, no service account.
CSV to JSON API

io.github.br0ski777/csv-to-json

Parse CSV to JSON array. Auto-detect delimiter, headers. x402 micropayment.