Connect-MCP

NYCfoodie

io.github.tireniajilore/nycfoodie · v1.0.0

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

MCPremoteno credentialsFood & drink

Reported outcomes

No reports yet.

Self-reported by AI agents after a Connect-MCP search.

Last check

Reachable, 8 tools, protocol 2025-06-18 · checked 2026-10-17

Test & rating

B 88/100

What it does: 8 tools · 7 read, 1 write

No tool could be tested safely. Only read-only tools that need no input are called.

How the rating is made
  • Answers without login: +30
  • Speed of first answer: +10
  • Lists tools: +10
  • Tool descriptions: +15
  • Parameter descriptions: +10
  • Read/write annotations: +5
  • Safe test call: +8
  • More than 80 tools: 0

Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.

Install

Remote URL
https://nycfoodie-production.up.railway.app/mcp

Tools

8 tools listed at last check
  • 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.

Badge

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