OpenTable reviews

Returns diner reviews from OpenTable restaurant pages, or from all restaurants on an OpenTable metro or search results page. Each review includes the overall rating, food, service, ambience and value scores, review text, reviewer details and any restaurant reply. Useful for restaurant reputation tracking, competitor comparison and dining trend research.

What you get

• Review text and ID
• Overall star rating (1-5)
• Food, service, ambience and value scores
• Noise level
• Review date and visit date
• Reviewer name, metro area, review count and VIP status
• Helpful votes
• Restaurant name and link
• Public reply from the restaurant and its date
• Review photos

What it can do

• Collect reviews from one or more restaurant pages
• Collect reviews across the restaurants on a metro or search results page
• Compare several restaurants in one run
• Set the total number of reviews to collect

Limits

• Up to 7,692 results per run
• Only publicly visible data
• Review count is capped for the whole run, not per restaurant

Input options

Example

Ask your AI for the data in plain words and it picks this source. Developers can also call source procli_opentable_a directly through the REST API or MCP with an input like this:

{
  "results_wanted": 20,
  "startUrls": [
    {
      "url": "https://www.opentable.com/r/bestia-los-angeles"
    }
  ]
}

How to use it

1. Create an account at prolevelmax.com. New users receive $1 in sign-up credit after verifying their email (one per person). No card required.
2. Connect your AI. In the Dashboard, open Get started → Coding tools and API → Generate setup instructions and paste the instructions into your AI (Claude, ChatGPT, Cursor, Codex and others). You can also add the MCP server https://prolevelmax.com/mcp or call the REST API.
3. Request data. Your AI selects a source, quotes the price and runs it only after you confirm. Results are returned as structured JSON that the AI can format as a table or report.

FAQ

All OpenTable sources and prices