# Booking.com Score and Review Count, Free Lookup

**Use case:** 

Booking.com only, for five Las Vegas resorts: the ten-point guest score, the review count, the hotel's own name and city as Booking spells them and the link to the property page, each matched through Booking's autocomplete with a hotel-type guard so a district or landmark never stands in for a hotel. The five-point twin of the score makes it comparable with other sites. Free: no billable rows.

## Input

```json
{
  "hotelNames": [
    "Bellagio, Las Vegas",
    "The Venetian Resort, Las Vegas",
    "Caesars Palace, Las Vegas",
    "Wynn Las Vegas, Las Vegas",
    "MGM Grand, Las Vegas"
  ],
  "startUrls": [],
  "sources": [
    "booking"
  ],
  "language": "en",
  "country": "us",
  "sessions": 2,
  "perIp": 1,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

## Output

```json
{
  "hotel": {
    "label": "Hotel",
    "format": "string"
  },
  "hotel_name": {
    "label": "Hotel name",
    "format": "string"
  },
  "rating": {
    "label": "Rating",
    "format": "number"
  },
  "rating_scale": {
    "label": "Rating scale",
    "format": "integer"
  },
  "rating_5": {
    "label": "Rating 5",
    "format": "number"
  },
  "review_count": {
    "label": "Review count",
    "format": "integer"
  },
  "ranking": {
    "label": "Ranking",
    "format": "string"
  },
  "sub_scores": {
    "label": "Sub scores",
    "format": "object"
  },
  "stars": {
    "label": "Stars",
    "format": "number"
  },
  "city": {
    "label": "City",
    "format": "string"
  },
  "country": {
    "label": "Country",
    "format": "string"
  },
  "matched_by": {
    "label": "Matched by",
    "format": "string"
  },
  "matched_confidence": {
    "label": "Matched confidence",
    "format": "number"
  },
  "source_id": {
    "label": "Source id",
    "format": "string"
  },
  "source_url": {
    "label": "Source url",
    "format": "string"
  },
  "reviews_scraper": {
    "label": "Reviews scraper",
    "format": "string"
  }
}
```

## About this Actor

This example demonstrates how to use [Free Hotel Review Checker — Ratings From 6 Sites](https://apify.com/kestrel/hotel-reputation-checker.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/kestrel/hotel-reputation-checker.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
This Task's input is already configured above — use it as-is rather than inventing a new one.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/kestrel/hotel-reputation-checker.md

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).