# Michelin-listed restaurants in San Francisco

**Use case:** 

Every San Francisco restaurant OpenTable tags as a Michelin holder, best-rated first. Measured 29 Oct 2026: 24 rows, the complete matching set. No column repeats which award a row holds, so the award filter is the record of why a restaurant is in the list.

## Input

```json
{
  "mode": "search",
  "location": "San Francisco, CA",
  "q": "",
  "includeDetails": false,
  "includeMenu": false,
  "includeReviews": false,
  "includeAvailability": false,
  "sort": "rating",
  "cuisines": [],
  "neighborhoods": [],
  "priceBands": [],
  "awardTags": [
    "MICHELIN"
  ],
  "contextualPrompts": [],
  "wheelchairAccessible": false,
  "restaurantUrls": [],
  "restaurantNames": [],
  "reviewsPerRestaurant": 20,
  "reviewsSort": "newestReview",
  "time": "19:00",
  "partySize": 2,
  "maxItems": 50,
  "detailConcurrency": 8,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ],
    "apifyProxyCountry": "US"
  }
}
```

## Output

```json
{
  "id": {
    "label": "ID",
    "format": "text"
  },
  "name": {
    "label": "Name",
    "format": "text"
  },
  "url": {
    "label": "Profile URL",
    "format": "link"
  },
  "cuisines": {
    "label": "Cuisines",
    "format": "array"
  },
  "priceBand": {
    "label": "Price band",
    "format": "text"
  },
  "priceBandId": {
    "label": "Price band id",
    "format": "text"
  },
  "rating": {
    "label": "Rating",
    "format": "number"
  },
  "reviewCount": {
    "label": "Review count",
    "format": "number"
  },
  "neighborhood": {
    "label": "Neighbourhood",
    "format": "text"
  },
  "neighborhoodId": {
    "label": "Neighbourhood id",
    "format": "text"
  },
  "metroId": {
    "label": "Metro id",
    "format": "text"
  },
  "address": {
    "label": "Address",
    "format": "text"
  },
  "city": {
    "label": "City",
    "format": "text"
  },
  "state": {
    "label": "State",
    "format": "text"
  },
  "postalCode": {
    "label": "Postal code",
    "format": "text"
  },
  "country": {
    "label": "Country",
    "format": "text"
  },
  "latitude": {
    "label": "Latitude",
    "format": "number"
  },
  "longitude": {
    "label": "Longitude",
    "format": "number"
  },
  "images": {
    "label": "Photo URLs",
    "format": "array"
  },
  "photosCount": {
    "label": "Photos count",
    "format": "number"
  },
  "description": {
    "label": "Description",
    "format": "text"
  },
  "features": {
    "label": "Features",
    "format": "array"
  },
  "firstNextAvailableTime": {
    "label": "First next available",
    "format": "text"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The OpenTable Restaurant Scraper – Reviews, Ratings & Phone Numbers Actor is ready to run with the inputs already set for "Michelin-listed restaurants in San Francisco". [Sign up or log in](https://console.apify.com/create-task-from-example/bbb6PJoe6MsreJufI) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Michelin-listed restaurants in San Francisco" task

The OpenTable Restaurant Scraper – Reviews, Ratings & Phone Numbers Actor will start running based on the input automatically. You can also change all the input fields, like what this run does, location, and more, to match your specific use case.

### 3. Receive the "Michelin-listed restaurants in San Francisco" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as ID, name, profile url, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Michelin-listed restaurants in San Francisco" task via API](https://apify.com/rl1987/opentable-api-scraper.md).

## About this Actor

This example demonstrates how to use [OpenTable Restaurant Scraper – Reviews, Ratings & Phone Numbers](https://apify.com/rl1987/opentable-api-scraper.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/rl1987/opentable-api-scraper.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/rl1987/opentable-api-scraper.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).