MCP server

NYCfoodie

io.github.tireniajilore/nycfoodie

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

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

Website Source

At a glance

Type

MCP server

Publisher

Not verified

Status

Working at last check

Tools

8

Token cost

About 3,031 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http nycfoodie https://nycfoodie-production.up.railway.app/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.nycfoodie]
url = "https://nycfoodie-production.up.railway.app/mcp"

Gemini CLI

{"mcpServers":{"nycfoodie":{"httpUrl":"https://nycfoodie-production.up.railway.app/mcp"}}}

Cursor

{"mcpServers":{"nycfoodie":{"url":"https://nycfoodie-production.up.railway.app/mcp"}}}

VS Code

{"servers":{"nycfoodie":{"type":"http","url":"https://nycfoodie-production.up.railway.app/mcp"}}}

Antigravity

agy mcp add nycfoodie https://nycfoodie-production.up.railway.app/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"nycfoodie","server_url":"https://nycfoodie-production.up.railway.app/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"nycfoodie","server_url":"https://nycfoodie-production.up.railway.app/mcp"}

Tools

• compare_restaurants ~233 tokens
  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 ~282 tokens
  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 ~226 tokens
  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.
• get_restaurant ~507 tokens
  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
• guide_consensus ~242 tokens
  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
• search_restaurants ~780 tokens
  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
• submit_feedback ~185 tokens
  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.
• top_rated ~576 tokens
  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.

Browse

• GitHub tools
• Booking and scheduling
• GitHub and code hosting

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