# Tripadvisor Restaurants Scraper (`boncross/tripadvisor-restaurants-scraper`) Actor

Scrape every restaurant Tripadvisor lists for a city. Just add a city and get name, rating, review count, cuisines, price level, address, phone, coordinates, opening hours, menu link, awards and reservation details. Filter by cuisine, diet, meal, price, rating and neighbourhood.

- **URL**: https://apify.com/boncross/tripadvisor-restaurants-scraper.md
- **Developed by:** [BonCross API](https://apify.com/boncross) (community)
- **Categories:** Travel
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 1,000 restaurant-listeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

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 examples already wired to this Actor's own input schema, see the [API](#api) section below.

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`).

# README

## Tripadvisor Restaurants Scraper

### What is Tripadvisor Restaurants Scraper?

Tripadvisor stops a restaurant list at 10,000, and Paris has 19,828. Tripadvisor Restaurants Scraper keeps going: it returned 19,200 of them in about four and a half minutes. Give it a city and you get its restaurants with the rating, cuisines, price level, address, phone, coordinates and the week's opening hours for each.

You'd use this one to build the list. When you want everything about one restaurant, Tripadvisor Place Details takes the same ids, and Tripadvisor Reviews returns what diners wrote.

Three things make the list worth having:

- **Size.** One city in full, past the 10,000 a single Tripadvisor list shows. 96.8% of Paris came back.
- **Fifteen filters.** Cuisine, establishment type, dietary option, meal, dish, feature, "good for", MICHELIN Guide, neighbourhood, rating, award, price level, open now, online reservations and online delivery. You pay only for the restaurants that match.
- **Opening hours you can compute with.** Each day is a list of opening and closing times, filled on 100% of 420 restaurants across 14 cities.

It costs $1.60 per 1,000 restaurants on the Free plan and $1.00 on Business, with nothing else to pay.

**BonCross Verified** means we tested this actor against the live site before release and kept the record:

- 37 of 37 live checks on its inputs and filters passed on 7 October 2026
- 12 cities run the same day: 289 restaurants, none empty
- Charges checked against the 289 rows
- A name that matches the wrong city gets an uncharged row saying so

### What data can you extract?

| Field | Description |
|---|---|
| 🏷️ Name | The restaurant's name on Tripadvisor |
| ⭐ Rating | The overall score out of five |
| Reviews | How many reviews the restaurant has |
| 🍣 Cuisines | The cuisines Tripadvisor lists for it |
| Establishment type | Restaurant, bakery, café, bar and so on |
| 💲 Price level | $, $$ - $$$ or $$$$ |
| 🕐 Opening hours | Each day's opening and closing times |
| Open now | Whether it is open as the run starts, and the site's wording |
| 🏠 Address | Full address, postcode and country |
| ☎️ Phone | As the restaurant publishes it |
| 📍 Coordinates | Latitude and longitude |
| 📖 Menu | A link to the menu, where one is listed |
| 📅 Reservations | Whether it takes online bookings, and through whom |
| 🛵 Delivery | Whether it offers online delivery |
| 🏆 Award | Travelers' Choice or Best of the Best, and the year |
| 💬 Review snippets | Two short quotes with links to the reviews |
| 🖼️ Photo | The lead photo |
| 🔗 Link | The restaurant's Tripadvisor page |

### How much does it cost to scrape Tripadvisor restaurants?

| Event | Free plan | Starter | Scale | Business |
|---|---|---|---|---|
| `actor-start`, per run | $0.001 | $0.001 | $0.001 | $0.001 |
| `city-checked`, per city that returns no restaurant (all of them filtered out) | $0.0005 | $0.0005 | $0.0005 | $0.0005 |
| `restaurant-listed`, per restaurant | $0.0016 | $0.00144 | $0.00125 | $0.001 |

Enterprise plans pay the Business price.

**$1.60 per 1,000 restaurants** on the Free plan, $1.00 on Business. There's no proxy to set up and no proxy charge, and platform usage is included.

- One city, first 1,000 restaurants: $0.001 + 1,000 × $0.0016 = **$1.601** ($1.00 on Business).
- The whole of Paris (19,200 rows): $0.001 + 19,200 × $0.0016 = **$30.721** ($19.20 on Business).

A city that couldn't be listed, or a name we refused, costs nothing. If a city was listed but your filters left no restaurant in it, you pay the $0.0005 `city-checked` fee once.

On Apify's Free plan, the $5 of monthly credits covers about 3,100 restaurants.

### How to scrape Tripadvisor restaurants

There's no code to write.

1. [Open a free Apify account](https://console.apify.com/sign-up) and go to [Tripadvisor Restaurants Scraper](https://apify.com/boncross/tripadvisor-restaurants-scraper).
2. Enter one or more cities: a name, a Tripadvisor link, or an id such as g187147.
3. Pick a sort and any filters, and say how many restaurants you want per city.
4. Press Start.
5. Download the list as Excel, CSV or JSON.

### ⬇️ Input

All you have to enter is a city.

Type its name, in English or in the city's own script (`Paris`, `東京`, `서울`, `Москва`), or paste a Tripadvisor link for any page of the city, or give its id (`g187147`). A close misspelling such as `Pari` still finds Paris. The city each name resolved to is written on the rows. For a name in a third language (`Londres`) or one that many places share, the link or the id is safer. "Start URLs (bulk upload)" takes the same links from a file or a Google Sheet.

"Maximum restaurants per city" (default 100) decides how many restaurants each city returns. Zero means all of them. "Maximum restaurants for the whole run" caps the total across your cities.

#### The 50 best-rated Japanese restaurants in Paris

```json
{
  "locations": ["https://www.tripadvisor.com/Restaurants-g187147-Paris_Ile_de_France.html"],
  "cuisines": ["Japanese"],
  "sortBy": "highestRated",
  "maxItemsPerLocation": 50
}
```

#### Fine dining in two cities, bookable online

```json
{
  "locations": ["New York City", "g186338"],
  "priceLevels": ["fineDining"],
  "onlyWithReservations": true,
  "maxItemsPerLocation": 200
}
```

#### The complete list for a city

```json
{
  "locations": ["g187147"],
  "maxItemsPerLocation": 0
}
```

#### The filters

Filters take the labels Tripadvisor shows on the city's Restaurants page, or their ids. If you use a label that city doesn't offer, the city stops with a row listing the labels it does offer.

| Input | Examples and options |
|---|---|
| `establishmentTypes` | Restaurants, Bakeries, Coffee & Tea, Bars & Pubs, Dessert, Quick Bites. Several are combined with OR. Empty means restaurants |
| `cuisines` | Japanese, Italian, French, Indian, Seafood. Several are combined with OR |
| `dietaryRestrictions` | Vegetarian friendly, Vegan options, Gluten free options, Halal, Kosher |
| `mealTypes` | Breakfast, Brunch, Lunch, Dinner, Late Night, Drinks |
| `features` | Takeout, Outdoor Seating, Reservations, Wheelchair Accessible, Serves Alcohol |
| `dishes` | A dish the restaurant is known for: Foie gras, Pizza, Sushi, Ramen |
| `goodFor` | Families with children, Romantic, Business meetings, Large groups, Scenic view |
| `michelinGuide` | MICHELIN 1 Star, MICHELIN 2 Stars, MICHELIN Bib Gourmand, MICHELIN Guide (any) |
| `neighborhoods` | Neighbourhood names as the city's Restaurants page lists them, for example Le Marais |
| `minRating` | Restaurants rated at least this out of 5: `"3"`, `"4"` or `"5"` |
| `awards` | `travelersChoice` and/or `bestOfTheBest`. Both together means either award |
| `priceLevels` | `cheapEats`, `midRange` and/or `fineDining` |
| `openNow` (default false) | Restaurants open when the run starts, in the city's local time |
| `onlyWithReservations` / `onlyWithDelivery` (default false) | Restaurants that take reservations or offer delivery online |

The minimum rating is Tripadvisor's own rating filter, which works on rounded ratings: a restaurant rated 4.6 can appear under a minimum of 5.

You can sort in Tripadvisor's "Featured" order (the default) or by highest rating.

#### For developers

- `maxItemsPerLocation` (default 100, 0 for all) applies per city, `maxItems` (default 0, no cap) to the run.
- Setting `maxItemsPerLocation` above 10,000, or to 0, continues past the 10,000-restaurant list neighbourhood by neighbourhood and removes the restaurants listed twice.
- If Tripadvisor answers a name with a different place that shares only a word with it (`Asdfgh City` comes back as New York City), the run refuses the match, writes an error row and charges nothing for that input.
- A city entered twice, say by name and by id, is listed once, under whichever input came first.
- With `onlyWithReservations` or `onlyWithDelivery`, a city that keeps nothing stops early: after 5 pages in a row with no restaurant kept, or after about three times the pages `maxItemsPerLocation` needs.

### ⬆️ Output

Restaurants arrive one per row, in the order of the sort you picked.

```json
{
  "id": "33226801",
  "locationId": 33226801,
  "name": "Osteria Degli Amici",
  "url": "https://www.tripadvisor.com/Restaurant_Review-g187147-d33226801-Reviews-Osteria_Degli_Amici-Paris_Ile_de_France.html",
  "rating": 4.8,
  "ratingScale": 5,
  "totalReviews": 63,
  "cuisines": ["Italian", "Mediterranean", "Healthy", "Romana", "Lazio"],
  "establishmentTypes": ["Restaurants"],
  "priceLevelText": "$$ - $$$",
  "isOpenNow": true,
  "openStatusText": "Open now",
  "openingHours": {
    "mon": [{ "open": "18:30", "close": "22:30" }],
    "tue": [{ "open": "12:00", "close": "22:30" }],
    "…": "…"
  },
  "address": "14 Rue Mandar, 75002 Paris France",
  "postcode": "75002",
  "country": "France",
  "phone": "+33 9 85 21 54 78",
  "lat": 48.865772,
  "lng": 2.345326,
  "menuUrl": "https://www.osteriadegliamici.fr/_files/ugd/9c307b_6ea2d60d63834963a0adcd55c7512710.pdf",
  "hasReservation": true,
  "reservationProvider": "TheFork",
  "hasDelivery": false,
  "award": "travelersChoice",
  "awardYear": 2026,
  "isPremium": true,
  "reviewSnippets": [{ "text": "Great restaurant", "url": "https://www.tripadvisor.com/ShowUserReviews-g187147-d33226801-r1074273238-Osteria_Degli_Amici-Paris_Ile_de_France.html" }],
  "photoUrl": "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/…jpg?w=1200&h=800&s=1",
  "totalResults": 10000,
  "searchGeoId": 187147,
  "searchGeoName": "Paris",
  "input": "g187147",
  "position": 2,
  "scrapedAt": "2026-10-04T18:46:30.086Z"
}
```

| Column | Meaning |
|---|---|
| `id`, `locationId` | Tripadvisor's id for the restaurant, as text and as a number. It joins with the Tripadvisor reviews and place details scrapers |
| `totalReviews` | The restaurant's review count |
| `openingHours` | `mon` … `sun`, each a list of `{open, close}` in local 24-hour time. An empty list is a closed day |
| `isOpenNow`, `openStatusText` | Open as the run starts ("Closes in 20 min" counts as open), and the site's wording |
| `hasReservation`, `reservationProvider`, `hasDelivery` | Online booking and delivery. Empty where Tripadvisor shows no booking block |
| `award`, `awardYear` | `travelersChoice` or `bestOfTheBest` |
| `isPremium` | Tripadvisor's flag for a restaurant with an enhanced owner listing |
| `totalResults` | How many restaurants matched the search on Tripadvisor (the site counts up to 10,000) |
| `searchGeoId`, `searchGeoName` | The city searched, as resolved from your input |
| `position` | Order in the list for that city |
| `input`, `error` | What you asked for and, on a row for a city that could not be listed, why |

#### How often each column is filled

We measured the first 30 restaurants in each of 14 cities on five continents, 420 in all, on 4 October 2026.

| Column | Filled |
|---|---|
| Name, link, rating, reviews, coordinates, address, price level, opening hours, photo, review snippets | 100% |
| Cuisines | 99% |
| Phone | 98% |
| Postcode | 95% |
| Award | 66% |
| Menu link | 61% |
| Reservations, delivery | 38% |

### How do you get past 10,000 restaurants, and how long does it take?

| Run | Restaurants | Time |
|---|---|---|
| One city, first 100 | 100 | 8 s |
| 14 cities, 30 each | 420 | 4 s of scraping, about 10 s in all |
| One city, first 1,000 | 1,000 | 7 s |
| The whole of Paris | 19,200 | about 4.5 minutes |

Tripadvisor shows at most 10,000 restaurants in one list. Set "Maximum restaurants per city" above 10,000, or to zero, and the run carries on neighbourhood by neighbourhood once the list ends, dropping the restaurants it has already returned. Paris counts 19,828 restaurants and returned 19,200 of them.

Be aware of where this stops. The neighbourhood lists cover most of a city, not all of it, and the share falls in the very largest cities.

### Who uses a city's restaurant list?

Sales teams prospecting restaurants by price level, neighbourhood or booking provider. People building a restaurant database or a city guide, best-rated first. Delivery and travel apps that need opening hours. Researchers mapping a cuisine across cities, or finding the vegan-friendly, halal or gluten-free options in a destination. If you track Travelers' Choice winners year by year, the award and its year are on the row.

To run it from your own code, send the input JSON to `https://api.apify.com/v2/acts/boncross~tripadvisor-restaurants-scraper/run-sync-get-dataset-items` and the rows come back in the response for a short run. A full-city run is better started and collected later. AI agents reach it through the Apify MCP server as the tool `tripadvisor-restaurants-scraper`.

### Limitations

- You need a city. Regions and countries aren't restaurant lists. A country returns a row naming its biggest cities for you to use.
- There's no search around a point for restaurants.
- Past 10,000 restaurants, coverage depends on the city's neighbourhood lists (96.8% in Paris).
- The "Featured" order is Tripadvisor's. "Highest rating" weighs review counts as well, which means it isn't strictly by rating.
- Just after midnight local time, Tripadvisor's open-now filter can still include a place that closed late the night before. The row reports the status Tripadvisor shows.
- Text is in English.
- You get one lead photo and two review snippets per restaurant. A snippet can end in "...", as Tripadvisor shows it.
- Phone numbers are as each restaurant publishes them, and formats differ.

### FAQ

#### How do I get more than 10,000 restaurants?

Set "Maximum restaurants per city" above 10,000, or to zero for all of them. That's the only switch.

#### Which filter labels can I use?

The ones on the city's Tripadvisor Restaurants page. Cities differ: a label the city doesn't offer returns a row listing the ones it does.

#### Why is there a 4.6 in my 5-rated list?

Tripadvisor's rating filter works on the rounded bubbles it displays, not on the exact score, and a 4.6 can come through under a minimum of 5. Of 60 Paris restaurants on 7 October 2026, 59 were rated 5.0 and one 4.6. London gave 59 and one 4.9. You get the list as Tripadvisor filters it. The exact `rating` is on each row if you want to cut more strictly yourself.

#### I typed a city and got the wrong place, or an error row. What happened?

A name goes to the best-known destination called that. One in a third language can match a smaller place spelled the same way ("Londres" is also a town in Argentina). When Tripadvisor answers with a place that merely shares a word with what you typed, we refuse the match and you get a free row naming the place it would have been. The link or the id avoids both, because neither goes through the name check.

#### What if I list the same city twice?

It's listed once, under the first of your inputs.

#### Do I need proxies or a Tripadvisor account?

You don't need either one. Nothing is signed in to, and proxy usage is included.

#### Is it legal to scrape Tripadvisor restaurant listings?

These are listings Tripadvisor shows to anyone, signed in or not. Collecting public data is broadly lawful, and what you do with it is your responsibility under GDPR and similar rules. If you're unsure, ask a lawyer.

### More from BonCross

- [Tripadvisor Attractions Scraper](https://apify.com/boncross/tripadvisor-attractions-scraper): The things to do Tripadvisor lists for a city or around a point.
- [Tripadvisor Hotels Scraper](https://apify.com/boncross/tripadvisor-hotels-scraper): Every hotel Tripadvisor lists for a city, with nightly prices for your dates and guests.
- [Tripadvisor Place Details Scraper](https://apify.com/boncross/tripadvisor-location-details): The full Tripadvisor record for any hotel, restaurant or attraction.
- [Tripadvisor Reviews Scraper](https://apify.com/boncross/tripadvisor-reviews): Every Tripadvisor review for any hotel, restaurant, attraction or tour.
- [Tabelog Restaurant Scraper](https://apify.com/boncross/tabelog-restaurant): Full Tabelog (食べログ) restaurant records by URL or id, in English, Korean, Chinese or Thai.
- [Tabelog Reviews Scraper](https://apify.com/boncross/tabelog-reviews): Tabelog (食べログ) restaurant reviews by URL or id: every 口コミ with overall and five…

### Your feedback

Missing a restaurant you can see on Tripadvisor, or a filter label that should work and doesn't? Open an issue on the Issues tab in Apify Console and name the city. We read them and reply there.

# Changelog

This Actor's version history is a separate document: https://apify.com/boncross/tripadvisor-restaurants-scraper/changelog.md

# Actor input Schema

## `locations` (type: `array`):

The cities to list restaurants for. Paste a Tripadvisor link for the city (any page of it, for example its Restaurants page), its id (g187147), or its name (Paris, 東京, New York City). Regions and countries are not lists: give a city.

## `startUrls` (type: `array`):

Tripadvisor city links, with the option to load them in bulk from a file, a Google Sheet or a remote list. Combined with anything in the list above.

## `maxItemsPerLocation` (type: `integer`):

How many restaurants to return for each city, in the order of the sort you pick. Zero means every one the site lists.

## `maxItems` (type: `integer`):

A run-wide ceiling on restaurants, across every city. Zero means no limit.

## `sortBy` (type: `string`):

Featured is Tripadvisor's default order. Highest rating puts the best-rated first, weighing how many reviews each has.

## `establishmentTypes` (type: `array`):

For example Restaurants, Bakeries, Coffee & Tea, Bars & Pubs, Dessert, Quick Bites. Several are combined with OR. Empty means restaurants (the site's default).

## `cuisines` (type: `array`):

For example Japanese, Italian, French, Indian, Seafood. Several are combined with OR.

## `dietaryRestrictions` (type: `array`):

For example Vegetarian friendly, Vegan options, Gluten free options, Halal, Kosher.

## `mealTypes` (type: `array`):

For example Breakfast, Brunch, Lunch, Dinner, Late Night, Drinks.

## `features` (type: `array`):

For example Takeout, Outdoor Seating, Reservations, Wheelchair Accessible, Serves Alcohol.

## `dishes` (type: `array`):

A dish the restaurant is known for, for example Foie gras, Pizza, Sushi, Ramen.

## `goodFor` (type: `array`):

For example Families with children, Romantic, Business meetings, Large groups, Scenic view.

## `michelinGuide` (type: `array`):

For example MICHELIN 1 Star, MICHELIN 2 Stars, MICHELIN 3 Stars, MICHELIN Bib Gourmand, MICHELIN Guide (any).

## `neighborhoods` (type: `array`):

Neighbourhood names as the city's Restaurants page lists them, for example Le Marais.

## `minRating` (type: `string`):

Tripadvisor's own rating filter, out of 5. It works on rounded ratings, so a restaurant rated 4.6 can appear under a minimum of 5.

## `awards` (type: `array`):

Only award winners. Both together means either award.

## `priceLevels` (type: `array`):

Only restaurants at these price levels.

## `openNow` (type: `boolean`):

Only restaurants open at the moment the run starts, in the city's own time.

## `onlyWithReservations` (type: `boolean`):

Only restaurants that take reservations online through Tripadvisor.

## `onlyWithDelivery` (type: `boolean`):

Only restaurants with online delivery.

## Actor input object example

```json
{
  "locations": [
    "g187147"
  ],
  "startUrls": [],
  "maxItemsPerLocation": 100,
  "maxItems": 0,
  "sortBy": "featured",
  "establishmentTypes": [
    "Bakeries"
  ],
  "cuisines": [
    "Japanese"
  ],
  "dietaryRestrictions": [
    "Vegan options"
  ],
  "mealTypes": [
    "Breakfast"
  ],
  "features": [
    "Takeout"
  ],
  "dishes": [
    "Pizza"
  ],
  "goodFor": [
    "Romantic"
  ],
  "michelinGuide": [
    "MICHELIN 1 Star"
  ],
  "neighborhoods": [
    "Le Marais"
  ],
  "openNow": false,
  "onlyWithReservations": false,
  "onlyWithDelivery": false
}
```

# Actor output Schema

## `dataset` (type: `string`):

Tripadvisor restaurants: every row the run returned.

## `stats` (type: `string`):

Counts for the run: cities resolved, pages fetched, rows returned.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "locations": [
        "https://www.tripadvisor.com/Restaurants-g187147-Paris_Ile_de_France.html"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("boncross/tripadvisor-restaurants-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "locations": ["https://www.tripadvisor.com/Restaurants-g187147-Paris_Ile_de_France.html"] }

# Run the Actor and wait for it to finish
run = client.actor("boncross/tripadvisor-restaurants-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "locations": [
    "https://www.tripadvisor.com/Restaurants-g187147-Paris_Ile_de_France.html"
  ]
}' |
apify call boncross/tripadvisor-restaurants-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,boncross/tripadvisor-restaurants-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/RfCJDHuUYQ9Ozy3z3/builds/sQ8iCQBnfUB5AHeFM/openapi.json