# NYCfoodie (remote · nycfoodie-production.up.railway.app)

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

- Trust score: 67/100 (medium)
- Change this week: +3
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-09-29

## Components

- remote · `nycfoodie-production.up.railway.app`: 67/100 (this document), [markdown](https://verifymcp.io/servers/tireniajilore-nycfoodie/nycfoodie-production.md), [page](https://verifymcp.io/servers/tireniajilore-nycfoodie/nycfoodie-production)

## Channel facts

- Endpoint: `https://nycfoodie-production.up.railway.app/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `1.0.0`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-09-29.

- **Endpoint Security**: 57/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - Authorisation not fully verified: no authorisation is required to call this server, and 1 tool(s) never declared a destructiveHint. The MCP spec treats an absent hint as destructive by default, so we cannot call this surface safe.
  - HTTPS is enforced; there's no plaintext access path.
  - HSTS check failed: the Strict-Transport-Security header is absent.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 66/100
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 1941 tokens (~242/item across 8 items; 8 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 30/100
  - Stability observed for 9 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 8 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 8 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### How do I install the NYCfoodie MCP server?

NYCfoodie is a hosted endpoint at https://nycfoodie-production.up.railway.app/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add --transport http tireniajilore-nycfoodie 'https://nycfoodie-production.up.railway.app/mcp'
```

### Cursor

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

### VS Code

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

### Codex

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

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "tireniajilore-nycfoodie": {
      "type": "remote",
      "url": "https://nycfoodie-production.up.railway.app/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add tireniajilore-nycfoodie --url 'https://nycfoodie-production.up.railway.app/mcp' --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  tireniajilore-nycfoodie:
    url: "https://nycfoodie-production.up.railway.app/mcp"
```

### Netclaw

```json
{
  "McpServers": {
    "tireniajilore-nycfoodie": {
      "Transport": "http",
      "Url": "https://nycfoodie-production.up.railway.app/mcp"
    }
  }
}
```

### Vellum

```bash
assistant mcp add tireniajilore-nycfoodie -t streamable-http -u 'https://nycfoodie-production.up.railway.app/mcp'
```

### Other

```json
{
  "mcpServers": {
    "tireniajilore-nycfoodie": {
      "type": "http",
      "url": "https://nycfoodie-production.up.railway.app/mcp"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-09-29 (score 67, +1)

No change was recorded against any check on this day. Stability & Change Management went from 27 to 30. That category is still filling its 30-day observation window: 8 days of observed history at the previous scan, 9 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-28 (score 66, 0)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-09-27 (score 66, +1)

No change was recorded against any check on this day. Stability & Change Management went from 20 to 23. That category is still filling its 30-day observation window: 6 days of observed history at the previous scan, 7 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-25 (score 65, 0)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-09-24 (score 65, +1)

No change was recorded against any check on this day. Stability & Change Management went from 10 to 13. That category is still filling its 30-day observation window: 3 days of observed history at the previous scan, 4 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-22 (score 64, +1)

- [security] Tool “compare_restaurants” rewrote its description, which is the text the model reads
- [security] Tool “get_restaurant” rewrote its description, which is the text the model reads
- [cosmetic] “compare_restaurants” added an optional parameter “ids”
- [cosmetic] “find_similar” added an optional parameter “name”
- [cosmetic] “get_restaurant” added an optional parameter “name”
- [cosmetic] “compare_restaurants” made “restaurants” optional
- [cosmetic] “find_similar” made “id” optional
- [cosmetic] “get_restaurant” made “id” optional

### 2026-09-21 (score 63, 0)

- [security] Tool “find_similar” rewrote its description, which is the text the model reads
- [security] Tool “get_restaurant” rewrote its description, which is the text the model reads
- [security] Tool “guide_consensus” rewrote its description, which is the text the model reads
- [security] Tool “search_restaurants” rewrote its description, which is the text the model reads
- [functional regression] Schema quality: 204 → 230
- [functional improvement] Stability: unverified → 0.03
- [cosmetic] “search_restaurants” reworded the description of “occasion”
- [cosmetic] “top_rated” reworded the description of “occasion”

### 2026-09-20 (score 63)

First indexed and scored.

## MCP tools (8)

### `search_restaurants` (~528 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 guide blurbs (e.g. 'cacio e pepe'). Returns compact matches with Infatuation rating (0–10), price tier, address_line and tags. Cards carry guide_appearance_count (a number); get_restaurant's guide_appearances is the full entry list. Known-closed venues are excluded by default. Coverage for city='new-york' is the five boroughs plus the immediate metro (within 30 km of Manhattan). With no query or filters, returns the highest-rated venues.

Input parameters:

- `city` (string, required): City slug, always required. Currently 'new-york', covering the five boroughs plus the immediate metro (within 30 km of Manhattan).
- `cuisine` (string): e.g. 'Italian', 'ramen'
- `include_closed` (boolean): Include known-closed venues (default false)
- `lat` (number): Latitude for proximity search. Must be given together with lng; radius_km defaults to 5 km when omitted. A location outside the NYC coverage area is rejected with an error.
- `limit` (integer): Max results (default 10)
- `lng` (number): Longitude for proximity search. Must be given together with lat; radius_km defaults to 5 km when omitted.
- `min_rating` (number): Minimum Infatuation rating
- `neighborhood` (string): e.g. 'West Village', or a borough like 'Brooklyn'
- `occasion` (string): Occasion tag. Allowed: 'Date Nights', 'Happy Hours', 'Pre-Theater', 'See & Be Seen', 'Serious Takeout Operation', 'Unique Dining Experiences', 'Wasting Your Time & Money'. Hyphens, spaces and undersc…
- `price_tier` (integer): 1 ($) to 4 ($$$$)
- `query` (string): Free text, e.g. 'date-night Italian'
- `radius_km` (number): Search radius in kilometres (default 5 when lat/lng are given without it). Requires lat and lng.
- `sort` (string): Sort by rating (default) or guide appearances

### `get_restaurant` (~352 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, URL, position, blurb, captured_at) for any venue with Eater guide entries — Eater-only venues have no rating or price, only this prose plus tags. Full review prose is opt-in via include_prose (default: headline and summary only). review.headline is the source's actual headline when one exists, otherwise null — use review.summary for the descriptive text. match_type is 'exact' when the id or name matched verbatim, 'fuzzy' when it was resolved from a partial/typo'd name — never present a fuzzy match as the venue the user named without saying so. booking is null when the source has no booking intel (not the same as walk-in-only); a reservation link alone never implies a booking policy. data_as_of is the dataset vintage and crawled_at is when this venue was last crawled — caveat fast-decaying claims (closures especially) when these are old.

Input parameters:

- `city` (string, required): City slug, always required. Currently 'new-york', covering the five boroughs plus the immediate metro (within 30 km of Manhattan).
- `id` (string): Canonical restaurant id, or a name to resolve
- `include_prose` (boolean): Include the full review text (default false: headline + summary only)
- `name` (string): Alias for id: the restaurant's exact name

### `compare_restaurants` (~122 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.

Input parameters:

- `city` (string, required): City slug, always required. Currently 'new-york', covering the five boroughs plus the immediate metro (within 30 km of Manhattan).
- `ids` (array): Alias for restaurants
- `restaurants` (array): Restaurant ids or names to compare

### `find_guides` (~165 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 and metadata without pulling every entry blurb.

Input parameters:

- `city` (string, required): City slug, always required. Currently 'new-york', covering the five boroughs plus the immediate metro (within 30 km of Manhattan).
- `include_entries` (boolean): Set false to return guide metadata without the ranked entry blurbs (default true)
- `limit` (integer): Max results (default 10)
- `query` (string): Theme, e.g. 'best ramen', 'date night'

### `find_similar` (~132 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.

Input parameters:

- `city` (string, required): City slug, always required. Currently 'new-york', covering the five boroughs plus the immediate metro (within 30 km of Manhattan).
- `id` (string): Canonical restaurant id, or a name to resolve
- `limit` (integer): Max results (default 10)
- `name` (string): Alias for id: the restaurant's exact name

### `guide_consensus` (~149 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 guide_appearances is the full entry list.

Input parameters:

- `city` (string, required): City slug, always required. Currently 'new-york', covering the five boroughs plus the immediate metro (within 30 km of Manhattan).
- `limit` (integer): Max results (default 10)
- `theme` (string): Guide theme, e.g. 'ramen', 'brunch'

### `top_rated` (~379 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.

Input parameters:

- `city` (string, required): City slug, always required. Currently 'new-york', covering the five boroughs plus the immediate metro (within 30 km of Manhattan).
- `cuisine` (string): e.g. 'Italian', 'ramen'
- `include_closed` (boolean): Include known-closed venues (default false)
- `lat` (number): Latitude for proximity search. Must be given together with lng; radius_km defaults to 5 km when omitted. A location outside the NYC coverage area is rejected with an error.
- `limit` (integer): Max results (default 10)
- `lng` (number): Longitude for proximity search. Must be given together with lat; radius_km defaults to 5 km when omitted.
- `min_rating` (number): Minimum Infatuation rating
- `neighborhood` (string): e.g. 'West Village', or a borough like 'Brooklyn'
- `occasion` (string): Occasion tag. Allowed: 'Date Nights', 'Happy Hours', 'Pre-Theater', 'See & Be Seen', 'Serious Takeout Operation', 'Unique Dining Experiences', 'Wasting Your Time & Money'. Hyphens, spaces and undersc…
- `price_tier` (integer): 1 ($) to 4 ($$$$)
- `radius_km` (number): Search radius in kilometres (default 5 when lat/lng are given without it). Requires lat and lng.

### `submit_feedback` (~114 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.

Input parameters:

- `comment` (string): What was good or wrong
- `rating` (integer): 1 (poor) to 5 (excellent)
- `tool` (string): Which tool the feedback is about, e.g. 'search_restaurants'

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/tireniajilore-nycfoodie/nycfoodie-production#diagnostics

## Score history

- 2026-09-29: 67
- 2026-09-28: 66
- 2026-09-27: 66
- 2026-09-26: 65
- 2026-09-25: 65
- 2026-09-24: 65
- 2026-09-23: 64
- 2026-09-22: 64
- 2026-09-21: 63
- 2026-09-20: 63

## Common questions

### What is the NYCfoodie MCP server?

NYCfoodie is an MCP server listed in the public MCP registry as io.github.tireniajilore/nycfoodie. Editorial NYC restaurant recommendations for AI agents: search, compare, guides, ratings. This page covers its hosted endpoint (https://nycfoodie-production.up.railway.app/mcp).

### Is the NYCfoodie MCP server safe to use?

NYCfoodie scores 67 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the NYCfoodie MCP server expose?

NYCfoodie exposes 8 tools: search_restaurants, get_restaurant, compare_restaurants, find_guides, find_similar, and 3 more. Their descriptions and schemas cost roughly 1,941 tokens of context every time the server is loaded.

### Does the NYCfoodie MCP server require authentication?

No. We connected to NYCfoodie without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.

### Is the NYCfoodie MCP server still maintained?

NYCfoodie is still listed as active in the MCP registry. We last reached this channel on 29 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

## Links

- Remote endpoint: https://nycfoodie-production.up.railway.app/mcp
- Repository: https://github.com/tireniajilore/nycfoodie
- Changelog RSS feed: https://verifymcp.io/servers/tireniajilore-nycfoodie/nycfoodie-production.xml
- Changelog JSON feed: https://verifymcp.io/servers/tireniajilore-nycfoodie/nycfoodie-production.json
- HTML version of this page: https://verifymcp.io/servers/tireniajilore-nycfoodie/nycfoodie-production