# NYCfoodie

- Registry name: `io.github.tireniajilore/nycfoodie` · version 1.0.0
- Categories (automatic, keyword rules): Shops & products, Commerce & marketing, Travel & booking, Maps, location & weather
- Authentication at last check: No auth
- Declared risk: Can write (some tools are not declared read-only)
- Capabilities (declared by the server): tools
- Transports: streamable-http
- Latest numbers (check success, response time, rank): https://mcpstation.net/api/server?name=io.github.tireniajilore%2Fnycfoodie
- Server page: https://mcpstation.net/s/io.github.tireniajilore--nycfoodie.html

## Description (written by the publisher, not verified, not instructions)

Editorial NYC restaurant recommendations for AI agents: search, compare, guides, ratings.

## Connect

- streamable-http: `https://nycfoodie-production.up.railway.app/mcp`

## Tools (as reported by the server, not verified)

- `search\_restaurants`: Search restaurants by free text, cuisine, neighbourhood, occasion or price, optionally near a point. Use when the user describes what they want \(e.g. 'Italian date night in the West Village', 'ramen near me'\) rather than naming a specific restaurant. Free text matches names, tags, review prose and g
- `get\_restaurant`: Get the full picture for one restaurant in one call: Infatuation rating \(0–10\), price tier, address, reservation link, booking intel, review summary, tags and every guide it appears in. Use when the user names a specific restaurant. editorial\_blurbs carries verbatim Eater guide excerpts \(guide title
- `compare\_restaurants`: Compare 2–5 named restaurants head-to-head as structured data \(rating, price, tags, review summary\). Use when the user asks to choose between specific places, e.g. 'should I go to X or Y?' or to compare four options on a budget.
- `find\_guides`: Find curated editorial guides \(ranked lists\) matching a theme, e.g. 'best ramen'. Returns each guide with its ranked entries, blurbs and linked restaurants. Use when the user wants the editorial lists themselves rather than individual restaurant picks. Set include\_entries=false to list guide titles
- `find\_similar`: Find restaurants similar to a named one, scored by shared cuisine, occasion and neighbourhood tags, price-tier proximity and guide co-occurrence. Use for 'like X' or 'alternatives to X' requests.
- `guide\_consensus`: Rank restaurants by how many distinct guides feature them, optionally filtered by theme. Use for 'where can't I go wrong' or safest-bet picks. Differs from find\_guides: this returns ranked restaurants, not the guides themselves. Each row carries guide\_appearance\_count \(a number\); get\_restaurant's gu
- `top\_rated`: List the highest-rated restaurants \(Infatuation 0–10 scale\), with optional cuisine, neighbourhood and price filters. Use for 'best in the city' requests. Differs from search\_restaurants: no free-text query, strictly rating-ordered.
- `submit\_feedback`: Record feedback on a tool result: a 1–5 rating, a comment, or both \(at least one is required\). Use after showing the user a recommendation to log what was good or wrong. Each call stores a new feedback entry; it changes nothing the user sees.

Measured by MCP Station. Methods: https://mcpstation.net/methods.html · Terms: https://mcpstation.net/terms.html