# Trustpilot Reviews Scraper API - Ratings, Replies & Dates (`scrapifier/trustpilot-reviews-scraper`) Actor

⚡ Scrape unlimited Trustpilot reviews for any company! Paste a domain or review URL, filter by stars, language, period or keywords, and instantly get rich, structured data — reviews, ratings, replies, TrustScores — for reputation monitoring, competitor analysis or lead generation.

- **URL**: https://apify.com/scrapifier/trustpilot-reviews-scraper.md
- **Developed by:** [Scrapifier](https://apify.com/scrapifier) (community)
- **Categories:** Business, Lead generation
- **Stats:** 2 total users, 1 monthly users, 96.3% runs succeeded, 1 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

$0.50 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## Trustpilot Reviews Scraper API - Ratings, Replies & Dates

Scrape customer reviews from Trustpilot by company name, domain or review URL and export them as JSON, CSV or Excel, or pull them straight from the API.

⚡ For every review you get the **star rating**, the **title and full text**, the publication and experience dates, the **verification status** and source, useful votes, the reviewer's display name, country and review count, the **company's reply** with its date, and the full **company profile**: TrustScore, rating distribution, categories, contact details (email, phone, address) and reply behaviour. **Server-side filters** for stars, language, period, keywords, topics, verified and replied reviews are applied by Trustpilot before you pay for a single review. Works on **any regional Trustpilot site**, with **no login and no cookies to paste**. You **pay per review**.

[![Apify Actor](https://apify.com/actor-badge?actor=scrapifier/trustpilot-reviews-scraper)](https://apify.com/scrapifier/trustpilot-reviews-scraper)

### 🎯 Why scrape Trustpilot reviews?

- **Reputation monitoring**: pull your own 1 and 2 star reviews every morning, check which ones the company answered, and track the TrustScore and rating distribution over time.
- **Competitor analysis**: scrape several brands in one run and compare ratings, review velocity, verification rate and reply behaviour side by side.
- **Lead generation**: the company profile carries the email, phone and postal address published on Trustpilot, plus categories, claimed status and review counts to qualify each prospect.
- **Customer insight**: filter reviews by keyword (`refund`, `delivery`) or by topic (`customer service`) to quantify what customers complain about or praise.
- **Market research and NLP**: build review datasets by language, reviewer country or period for sentiment analysis, topic modelling or academic work.
- **Due diligence**: TrustScore, consumer alerts, reply percentage and average days to reply are quick health signals for a partner or an acquisition target.

### 📊 What data does Trustpilot Reviews Scraper extract?

| Field | Description |
|---|---|
| `id` | Unique Trustpilot review id |
| `url` | Direct link to the review |
| `title`, `text` | Review title and full text |
| `rating` | Star rating (1 to 5) |
| `language` | Review language (ISO code) |
| `source` | How the review was collected (Organic, Invitation...) |
| `published_date`, `experienced_date` | Publication date and date of experience (ISO 8601) |
| `updated_date`, `submitted_date` | Last edit date and submission date, when provided |
| `verified`, `verification_level`, `verification_source` | Whether the review is verified, Trustpilot's verification level and its source |
| `is_pending` | Whether the review is still pending |
| `likes` | Number of useful votes |
| `consumer.*` | Reviewer: `id`, `display_name`, `country_code`, `number_of_reviews`, `is_verified`, `image_url`, `reviews_on_same_domain` |
| `reply.*` | The company's reply: `message` and `published_date`, or `null` when there is none |
| `product_reviews`, `location` | Product-specific details and the business location tied to the review, when present |
| `company.*` | Company profile (with `include_company_info`): `name`, `domain`, `trustpilot_url`, `website_url`, `trust_score`, `stars`, `number_of_reviews`, `number_of_reviews_last_12_months`, `is_claimed`, `consumer_alert`, `country_code`, `categories`, `category_path` |
| `company.contact.*` | `email`, `phone`, `address`, `city`, `country`, `zipcode` |
| `company.activity.*` | `claimed_date`, `reply_percentage`, `average_days_to_reply`, `verified_by_google`, `verified_payment_method` |
| `company.rating_distribution.*` | Review count per star: `total`, `one` to `five` |
| `scraped_at` | Extraction timestamp |
| `search_url` | The filtered review-page URL this review came from |

With `flatten_company_data` enabled, flat `company_name`, `company_domain`, `company_url`, `company_website`, `company_trust_score`, `company_stars`, `company_total_reviews` and `company_country_code` columns are added next to the nested object so CSV and Excel exports stay flat.

### 🚀 How to scrape Trustpilot reviews

1. Open the Actor and enter one or more companies in **Companies / URLs** (`company_urls`), one per row: a company name (`amazon`), a domain as shown on Trustpilot (`www.amazon.com`), a company website (`https://www.amazon.com`), a Trustpilot review URL or a reviewer profile URL (`https://www.trustpilot.com/users/{id}`). Regional hosts such as `fr.trustpilot.com` work too.
2. Optionally set **Review filters**: star ratings, languages, a rolling period or exact published dates, an exact keyword, topics, reviewer countries, verified only, with company reply only, and the sort order.
3. Set **Max reviews per company** (`100` by default, `0` = as many as available). Leave the proxy on Apify Residential.
4. Click **Start**. The Actor collects the filtered reviews, paging through the results, 20 reviews per page.
5. Open the **Storage** tab to preview the reviews and export them as JSON, CSV, Excel or XML, or read them from the dataset API.

The same run can be started from the Apify API, the Python or JavaScript client, or put on a schedule for daily or weekly monitoring.

### 📥 Input parameters

| Field | Key | Type | Default | Description |
|---|---|---|---|---|
| Companies / URLs | `company_urls` | array of strings | `["amazon"]` | Required. Company names, Trustpilot domains, company website URLs, Trustpilot review URLs (their own query filters are kept) or reviewer profile URLs, one per row. |
| Star ratings | `stars` | select (multiple) | none | Only reviews with these ratings: `1`, `2`, `3`, `4`, `5`. Empty = all ratings. |
| Languages | `languages` | select (multiple) | none | Languages to keep, 57 in the list (`en`, `fr`, `de`, `es`, `it`, `nl`, `pt`, `pl`, `ja`, `zh`...) or any ISO 639-1 code. Empty = all. |
| Period | `date` | select | `""` (All time) | Rolling window: `""` (All time), `last30days`, `last3months`, `last6months`, `last12months`. Combines with Published after. |
| Published after | `start_date` | string | none | Only reviews published on or after this date (`YYYY-MM-DD`). With the default sort the run stops as soon as it reaches older reviews. |
| Published before | `end_date` | string | none | Only reviews published on or before this date (`YYYY-MM-DD`). |
| Keywords (exact) | `search` | string | none | Only reviews containing this exact text (`refund`, `delivery`). |
| Topics (themes) | `topics` | array of strings | none | Only reviews about these themes, a broader semantic match than Keywords (`refund`, `customer service`, `delivery`). |
| Reviewer countries | `countries` | select (multiple) | none | Reviewer countries to keep, 249 in the list (`GB`, `US`, `FR`, `DE`, `ES`, `IT`, `NL`, `AU`, `CA`...) or any ISO 3166-1 alpha-2 code. Empty = all. |
| Verified reviews only | `verified` | boolean | `false` | Only reviews with a verified order or invitation. |
| With company reply only | `replies_only` | boolean | `false` | Only reviews the company has replied to. |
| Sort by | `sort` | select | `recency` | `recency` (most recent first) or `relevance` (most relevant first). |
| Expand regional domains | `expand_regional_domains` | boolean | `false` | After resolving a company, also scrape every regional sibling (amazon.com, amazon.co.uk, amazon.de...). The per-company limit applies to each sibling. |
| Strict name matching | `strict_name_match` | boolean | `false` | Reject search hits whose business name does not clearly match your query. Off = accept Trustpilot's top suggestion. |
| Max reviews per company | `max_reviews_per_company` | integer | `100` | Reviews to collect per company or reviewer. `0` = as many as available. |
| Include company profile | `include_company_info` | boolean | `true` | Attach the full company profile (TrustScore, rating distribution, category, review velocity, reply behaviour, contact details) to every review. |
| Flat company columns (CSV-friendly) | `flatten_company_data` | boolean | `false` | Add flat `company_name`, `company_domain`, `company_trust_score`... columns next to the nested `company` object. |
| Report empty inputs | `emit_input_status` | boolean | `true` | Add an `input_status` report to the run's OUTPUT record listing which inputs returned no reviews and why. |
| Proxy | `proxyConfiguration` | object | Apify Residential | Residential proxies are recommended for reliable runs. |

Example input:

```json
{
  "company_urls": ["www.amazon.com"],
  "stars": ["1", "2"],
  "languages": ["en"],
  "start_date": "2026-01-01",
  "max_reviews_per_company": 500,
  "include_company_info": true
}
```

A pasted Trustpilot review URL keeps its own query filters (for example `?stars=5`), which override the global filters for that company only. A bare domain that Trustpilot does not know (`amazon.com` instead of `www.amazon.com`) is resolved once through a name search; turn on `strict_name_match` if a company name resolves to an adjacent but wrong brand.

### 📤 Output example

Each review is one dataset item, exportable as JSON, CSV, Excel or via the API.

```json
{
  "id": "abc123",
  "url": "https://www.trustpilot.com/reviews/abc123",
  "title": "Fast delivery, great service",
  "text": "Ordered on Monday, arrived Wednesday. Very happy.",
  "rating": 5,
  "language": "en",
  "published_date": "2026-06-20T14:03:00Z",
  "verified": true,
  "likes": 2,
  "consumer": { "display_name": "John D.", "country_code": "GB", "number_of_reviews": 7 },
  "reply": { "message": "Thanks for your feedback!", "published_date": "2026-06-21T09:00:00Z" },
  "company": { "name": "Amazon", "domain": "www.amazon.com", "trust_score": 4.1, "number_of_reviews": 132045 },
  "scraped_at": "2026-06-25 10:00:00"
}
```

The run's OUTPUT record also holds the run statistics (companies, users, unique reviews, pages, duplicates, errors) and, per input, an `input_status` entry (`ok`, `empty` or `not_found`, with the resolved domain and a reason) so you can see at a glance which input produced nothing.

### 💡 Ready-to-run examples

**Negative English reviews published since a date**

```json
{ "company_urls": ["www.amazon.com"], "stars": ["1", "2"], "languages": ["en"], "start_date": "2026-01-01", "max_reviews_per_company": 500 }
```

**Latest 100 reviews of a company, by name**

```json
{ "company_urls": ["amazon"], "max_reviews_per_company": 100 }
```

**Reviews mentioning a keyword in the last 3 months**

```json
{ "company_urls": ["www.amazon.com"], "search": "refund", "date": "last3months", "sort": "recency" }
```

**A brand's regional sites, verified reviews with a company reply**

```json
{ "company_urls": ["amazon"], "expand_regional_domains": true, "verified": true, "replies_only": true, "max_reviews_per_company": 100 }
```

**A filtered Trustpilot review URL, with flat columns for Excel**

```json
{ "company_urls": ["https://www.trustpilot.com/review/www.amazon.com?stars=5"], "flatten_company_data": true, "max_reviews_per_company": 200 }
```

### 💰 Pricing: how much does it cost to scrape Trustpilot reviews?

**$0.50 per 1,000 reviews**, flat. You pay only for the results you receive, there is no subscription and no start fee. New Apify accounts get free monthly platform credits to try it.

Cost is driven purely by the number of reviews returned: use `max_reviews_per_company` to cap each company (with `expand_regional_domains` the cap applies to each regional domain), and narrow the set with `stars`, `languages`, `date`, `search`, `topics`, `verified` or `replies_only`, which Trustpilot applies before anything is fetched.

### ⚙️ Performance, proxies and limits

- **Residential proxies recommended.** Keep the default proxy on; a residential proxy gives the most reliable runs. The Apify `RESIDENTIAL` group is prefilled.
- **Pagination**: 20 reviews per page, fixed by Trustpilot. Results are pushed to the dataset every 5 pages, so partial data is available while the run is still going.
- **Server-side versus client-side filters**: stars, a single language, period, keywords, topics, verified, replies and sort are applied by Trustpilot. Reviewer countries, exact published dates and a selection of several languages are applied by the Actor after fetching, so they still consume pages even though you only pay for the reviews kept.
- **Early stop on dates**: with `start_date` and the default `recency` sort, the run stops at the first review older than the date. With `relevance` sort it pages through the whole filtered list.
- **Deduplication**: reviews are deduplicated by `id` within a run, and a company is closed after 3 consecutive pages without a new review.
- **Reviewer profiles**: user pages have no server-side filters. Stars, verified, countries, dates and languages are applied after fetching; keywords, topics and the reply filter do not apply, and the `company` block is limited to `id`, `name`, `domain` and `trustpilot_url`.
- **Empty inputs**: a name that resolves to nothing is reported as `not_found`, a company whose reviews are all filtered out as `empty`, in the `input_status` report of the OUTPUT record.
- **Default run options**: 2,048 MB of memory and a 3,600 second timeout. Raise the timeout for very large companies with `max_reviews_per_company` set to `0`.

### 🔌 Integrations and API

Run Trustpilot Reviews Scraper from the [Apify API](https://docs.apify.com/api/v2), the [Python](https://docs.apify.com/api/client/python) or [JavaScript](https://docs.apify.com/api/client/js) client, or on a [schedule](https://docs.apify.com/platform/schedules). Connect it to Make, Zapier, n8n, Google Sheets, Slack or any webhook through [Apify integrations](https://apify.com/integrations). Every run's dataset is available as JSON, CSV, Excel or XML from the dataset API.

```bash
curl -X POST "https://api.apify.com/v2/acts/scrapifier~trustpilot-reviews-scraper/run-sync-get-dataset-items?token=<YOUR_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{ "company_urls": ["www.amazon.com"], "stars": ["1", "2"], "languages": ["en"], "start_date": "2026-01-01", "max_reviews_per_company": 500 }'
```

### ❓ FAQ

**Is it legal to scrape Trustpilot reviews?**

The Actor only reads reviews and company profiles that Trustpilot publishes to anyone without logging in. Reviews contain personal data (reviewer names and countries), so process them in line with GDPR and other privacy laws, respect Trustpilot's terms of use, and stay responsible for how you use the data. This is not legal advice.

**Do I need a Trustpilot account, login or cookies?**

No. Nothing to log in to and no cookies to paste. Keep the prefilled Apify Residential proxy for reliable runs.

**Can I export Trustpilot reviews to Excel or Google Sheets?**

Yes. Every run's dataset downloads as CSV, XLSX, JSON or XML from the Storage tab, and the Google Sheets integration can push new reviews to a sheet automatically. Turn on `flatten_company_data` to get the company columns flat in the spreadsheet.

**How many reviews can I scrape per company?**

As many as Trustpilot exposes for your filters (set `max_reviews_per_company` to `0`). Most users cap each run, sort by `recency` and set `start_date` so that each scheduled run only fetches what is new.

**How do I target a specific country's Trustpilot site?**

Paste that country's Trustpilot review URL (`fr.trustpilot.com`, `uk.trustpilot.com`...), which keeps its regional host, or turn on `expand_regional_domains` to scrape every regional sibling of the brand in one run. To keep only reviews written from one country, use `countries` instead.

**Can I scrape the reviews written by one person?**

Yes. Paste that reviewer's profile URL (`https://www.trustpilot.com/users/{id}`) in `company_urls`. Stars, verified, countries, dates and languages still apply; keywords, topics and the reply filter do not.

**Why did my run return no reviews, or report being blocked?**

Check the `input_status` report in the OUTPUT record: `not_found` means the name or domain did not resolve on Trustpilot (try the exact domain shown on Trustpilot, such as `www.amazon.com`), `empty` means every review was filtered out. A blocked run usually means residential proxies are needed: keep the `RESIDENTIAL` group in `proxyConfiguration` and retry.

**How fresh is the data?**

Every run scrapes Trustpilot live. Schedule the Actor daily or weekly with `start_date` to keep a rolling history of new reviews.

### 🔗 Related scrapers

- [Glassdoor Reviews Scraper](https://apify.com/scrapifier/glassdoor-reviews-scraper): employee reviews with ratings, pros, cons, advice and company responses.
- [Glassdoor Company Overview Scraper](https://apify.com/scrapifier/glassdoor-company-scraper): the full company profile (ratings, CEO approval, size, HQ, revenue) by name or URL.
- [Glassdoor Company Search Scraper](https://apify.com/scrapifier/glassdoor-company-search-scraper): find companies by location, industry, minimum rating and size.
- [Quora Answers Scraper](https://apify.com/scrapifier/quora-scraper): answers, authors and upvotes for any Quora question.
- [Vinted Scraper](https://apify.com/scrapifier/vinted-scraper): second-hand fashion listings from any Vinted country.

### 💬 Support

Questions, bugs or a feature request? Open an issue in the **Issues** tab of this Actor, I answer quickly. If Trustpilot Reviews Scraper saves you time, a rating on the Store helps others find it.

# Actor input Schema

## `company_urls` (type: `array`):

One item per row. Each can be:

- a **company name** (`amazon`), resolved to the top Trustpilot match,
- a **domain** as shown on Trustpilot (`www.amazon.com`),
- a **company website URL** (`https://www.amazon.com`),
- a **Trustpilot review URL** (`https://www.trustpilot.com/review/…`, its own query filters are kept),
- a **reviewer profile URL** (`https://www.trustpilot.com/users/{id}`, scrapes the reviews that user wrote).
  Regional Trustpilot hosts (fr., uk., de.…) work too.

## `stars` (type: `array`):

Only reviews with these ratings. Empty = all ratings.

## `languages` (type: `array`):

Pick one or more languages to keep (or type any ISO 639-1 code). Empty = all languages.

## `date` (type: `string`):

Rolling date window. For an exact cutoff use 'Published after' below, the two combine.

## `start_date` (type: `string`):

Only reviews published on or after this date (YYYY-MM-DD). With the default 'Most recent' sort the run stops as soon as it reaches older reviews.

## `end_date` (type: `string`):

Only reviews published on or before this date (YYYY-MM-DD).

## `search` (type: `string`):

Only reviews containing this exact text (e.g. "refund", "delivery").

## `topics` (type: `array`):

Only reviews about these themes, a broader, semantic match than Keywords (e.g. "refund", "customer service", "delivery").

## `countries` (type: `array`):

Pick one or more reviewer countries to keep (or type any ISO 3166-1 alpha-2 code). Empty = all countries.

## `verified` (type: `boolean`):

Only reviews with a verified order / invitation.

## `replies_only` (type: `boolean`):

Only reviews the company has replied to.

## `sort` (type: `string`):

Review ordering.

## `expand_regional_domains` (type: `boolean`):

After resolving a company, also scrape every regional sibling on Trustpilot (e.g. amazon → amazon.com, amazon.co.uk, amazon.de…). The per-company limit applies to each sibling.

## `strict_name_match` (type: `boolean`):

Reject search hits whose business name doesn't clearly match your query (keeps adjacent-but-wrong brands out). Off = accept Trustpilot's top suggestion.

## `max_reviews_per_company` (type: `integer`):

How many reviews to collect per company / reviewer (0 = as many as available). With regional expansion this applies to each domain.

## `include_company_info` (type: `boolean`):

Attach the full company profile to every review: TrustScore, rating distribution, category, review velocity, reply behaviour, and contact details (email, phone, address).

## `flatten_company_data` (type: `boolean`):

Also add flat top-level columns (company_name, company_domain, company_trust_score…) next to the nested company object, ideal for CSV / Excel exports.

## `emit_input_status` (type: `boolean`):

Add an input_status report to the run's OUTPUT record listing which inputs returned no reviews and why (not found, empty, filtered out).

## `proxyConfiguration` (type: `object`):

Residential proxies are recommended for reliable runs.

## Actor input object example

```json
{
  "company_urls": [
    "amazon"
  ],
  "date": "",
  "verified": false,
  "replies_only": false,
  "sort": "recency",
  "expand_regional_domains": false,
  "strict_name_match": false,
  "max_reviews_per_company": 100,
  "include_company_info": true,
  "flatten_company_data": false,
  "emit_input_status": true,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

# Actor output Schema

## `reviews` (type: `string`):

All Trustpilot reviews extracted by this run.

# 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 = {
    "company_urls": [
        "amazon"
    ],
    "max_reviews_per_company": 100,
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "RESIDENTIAL"
        ]
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapifier/trustpilot-reviews-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 = {
    "company_urls": ["amazon"],
    "max_reviews_per_company": 100,
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
    },
}

# Run the Actor and wait for it to finish
run = client.actor("scrapifier/trustpilot-reviews-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 '{
  "company_urls": [
    "amazon"
  ],
  "max_reviews_per_company": 100,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}' |
apify call scrapifier/trustpilot-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapifier/trustpilot-reviews-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/tVq0bspPt14ItqTeG/builds/1jrBG5tLqFBRkJwh0/openapi.json