Editorial NYC restaurant recommendations for AI agents: search, compare, guides, ratings.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
One-click editor setup isnβt available for this listing yet β we donβt have a confirmed install command, and weβd rather show nothing than point your editor at the wrong package or host. Follow the projectβs own setup instructions, linked above.
The data layer for restaurant taste: structured, editorial restaurant recommendations served to AI agents over MCP. Not another review scraper β curated guides and reviews normalised into one schema, queryable by tools.
MVP city: New York. The city is a parameter everywhere; nothing NYC-specific is hardcoded.
Hosted endpoint (Streamable HTTP): https://nycfoodie-production.up.railway.app/mcp
claude mcp add --transport http nycfoodie https://nycfoodie-production.up.railway.app/mcpsearch_restaurants Β· get_restaurant Β· compare_restaurants Β· find_guides Β· find_similar Β· guide_consensus Β· top_rated Β· submit_feedback
db/ β SQLite storage (better-sqlite3) with numbered SQL migrations written in Postgres-compatible DDL. The migration runner is dialect-agnostic by convention, so a Postgres adapter can replace better-sqlite3 later without touching the migrations.crawler/ β source adapters (starting with The Infatuation) that normalise into the db schema. Endpoint/field mapping: docs/infatuation-data-surface.md (step 2).mcp/ β stdio MCP server (@modelcontextprotocol/sdk) exposing search, detail, comparison and guide tools.docs/infatuation-data-surface.md.NNN_name.sql, applied once in order; see db/migrations/README.md for the Postgres-compatibility rules.*.db files or credentials.No reviews yet β be the first to share how this listing worked for you.
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