# LinkedIn Jobs Scraper - Salary, Skills & Applicants (`parseforge/linkedin-jobs-scraper`) Actor

Scrape LinkedIn job postings by keyword, location and date posted, no login. 31 fields per job: company, salary min and max, applicant count, benefits, full description, skills, seniority, employment type, job function and industry. Each job ID once per run.

- **URL**: https://apify.com/parseforge/linkedin-jobs-scraper.md
- **Developed by:** [ParseForge](https://apify.com/parseforge) (community)
- **Categories:** Jobs, Developer tools
- **Stats:** 57 total users, 2 monthly users, 100.0% runs succeeded, 4 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

from $2.36 / 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.
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

[![ParseForge](https://raw.githubusercontent.com/ParseForge/apify-assets/main/banner-v4.webp)](https://apify.com/parseforge?fpr=vmoqkp)

### LinkedIn Jobs Scraper

**Returns LinkedIn job postings as flat rows with 31 fields each: title, company, location, posted date, salary min and max, applicant count, benefits, full description, skills, seniority, employment type, job function and industry.** No login, no cookies, no API key.

**Measured reliability:** 62 of 63 runs in the last 30 days succeeded (98.4%), 0 failed and 1 was aborted (Apify public run stats, 30-day window, read on 2026-09-24). A test run with the default input on 2026-09-24 returned 8 jobs with full details in 9.5 seconds.

LinkedIn's official API requires partner approval, OAuth tokens, and strict rate limits. This scraper reads the public job search pages directly. Keyword, location, company ID, date posted and Easy Apply go to LinkedIn's search. Job type, experience level, workplace type and minimum salary are checked by the Actor on each job page, because LinkedIn's logged-out search ignores them. It returns each match in one consistent schema, with optional full job descriptions and extracted skills.

| Who uses it | What they scrape LinkedIn for |
|---|---|
| Recruiters | Monitor competitor hiring volumes and job descriptions for specific roles. |
| Job boards | Aggregate listings from LinkedIn into a centralized search index. |
| Market analysts | Track which skills and experience levels are in demand by region. |
| Sales teams | Find companies that are hiring to identify new business opportunities. |

### Common complaints about LinkedIn job scrapers, and how this one handles them

These come from 1 and 2 star reviews of other LinkedIn job scrapers on the Apify Store. Each answer below was checked against a real run or the source code.

| Complaint | What this Actor does |
|---|---|
| Empty output, even after trying several inputs | The default input returned 8 full jobs on 2026-09-24. Over the last 30 days 62 of 63 runs succeeded and none failed. |
| Duplicate jobs in one run, each one charged again | Every job ID is kept in a set and written once per run. The 8 rows of the test run had 8 different job IDs, and the run charged exactly 8 results. |
| No company name in the output | `company`, `companySlug`, `companyLinkedInUrl` and `companyLogo` were filled on 8 of 8 rows in the test run. |
| Jobs posted weeks ago are shown with today's date | `postedDate` is read from the date LinkedIn prints on the listing, not from the time of the scrape. In the test run one job carried 2026-09-17 while the others carried 2026-09-24. |
| A keyword search returns a broad mix of job types | Job type, experience level, workplace type and minimum salary are checked on each job page, and only matching jobs are written and charged. In a test on 2026-09-24 a contract-only run returned 3 of 3 contract jobs, and a remote-only run returned 3 remote jobs after dropping 4 that did not match. Each row also carries `jobFunction` and `industries`. |

### What it does

This Actor collects LinkedIn job postings from a search query and location, and returns each one as a flat row with title, company, location, link, and optional full description, salary, skills, and raw HTML.

- 🔍 **Search by title and location:** Enter a job title or keyword and a city, state, country, or 'Remote'.
- 🏢 **Company ID:** Return only one company's jobs by its LinkedIn company ID.
- 📅 **Date filters:** Limit results to jobs posted in the past 24 hours, past week, or past month.
- 💼 **Job type and experience:** Keep only full-time, part-time, contract, internship and other types, and entry level through executive. Checked on each job page.
- 🏠 **Workplace type:** Keep only on-site, remote, or hybrid jobs, based on the workplace wording on each job page.
- ✅ **Easy Apply only:** Return only jobs that accept LinkedIn Easy Apply applications.
- 💰 **Minimum salary:** Keep only jobs with a published USD salary of at least $40k to $200k+ a year. Hourly and monthly pay are converted to yearly.
- 📄 **Full job details:** Fetch complete descriptions, company info, and salary data. This is on by default and is what fills the 31 fields.
- 🛠️ **Skill extraction:** Parse and return a list of skills mentioned in each job description.
- 📜 **Raw HTML:** Include the raw HTML of each job detail page for custom downstream parsing.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

### Output fields

Every row has the same 31 fields. The fill counts come from the 8-job test run with the default input on 2026-09-24. Fields LinkedIn does not publish for a job come back as `null`.

| Field | Type | Filled in test run | Description |
|---|---|---|---|
| `id` | string | 8/8 | LinkedIn job ID. |
| `title` | string | 8/8 | Job title. |
| `company` | string | 8/8 | Company name. |
| `companySlug` | string | 8/8 | Company handle in the LinkedIn URL. |
| `companyLinkedInUrl` | string | 8/8 | Company page on LinkedIn. |
| `companyLogo` | string | 8/8 | Company logo image URL. |
| `location` | string | 8/8 | Job location as LinkedIn shows it. |
| `link` | string | 8/8 | Job posting URL. |
| `postedDate` | string | 8/8 | Date the job was posted, `YYYY-MM-DD`. |
| `postedDateRaw` | string | 8/8 | Posted date as read from the listing. |
| `salary` | string | 7/8 | Short salary range, for example `$165K - $225K`. |
| `salaryRaw` | string | 7/8 | Salary text as LinkedIn prints it. |
| `salaryMin` | integer | 7/8 | Lower bound of the salary range. |
| `salaryMax` | integer | 7/8 | Upper bound of the salary range. |
| `salaryCurrency` | string | 7/8 | Currency code, for example `USD`. |
| `salaryPeriod` | string | 7/8 | `year`, `month` or `hour`. |
| `salaryIsEstimate` | boolean | 7/8 | True when the range is an estimate, not set by the employer. |
| `applicants` | integer | 8/8 | Applicant count. For "Be among the first 25 applicants" this is 25. |
| `applicantsRaw` | string | 8/8 | Applicant text as LinkedIn prints it. |
| `benefits` | array | 8/8 | Listed benefits, for example Dental, Vision, 401(k). |
| `description` | string | 8/8 | Full job description. |
| `descriptionText` | string | 8/8 | Description with whitespace cleaned. |
| `descriptionLength` | integer | 8/8 | Description length in characters. |
| `skills` | array | 8/8 | Skills found in the description. |
| `workType` | string | 7/8 | `Remote`, `Hybrid` or `On-site`. |
| `experienceLevel` | string | 8/8 | Seniority, for example `Mid-Senior level`. |
| `employmentType` | string | 8/8 | `Full-time`, `Part-time`, `Contract` and so on. |
| `jobFunction` | string | 8/8 | Job function, for example `Engineering and Information Technology`. |
| `industries` | string | 8/8 | Company industry. |
| `searchQuery` | string | 8/8 | The query and location that found the job. |
| `scrapedAt` | string | 8/8 | Time the row was collected, ISO 8601. |

A real row from the test run (description shortened):

```json
{
  "id": "4470016721",
  "title": "Software Engineer II, Backend (Identity Decisioning)",
  "company": "Affirm",
  "location": "St Louis, MO",
  "link": "https://www.linkedin.com/jobs/view/4470016721",
  "postedDate": "2026-09-24",
  "salary": "$165K - $225K",
  "salaryMin": 165000,
  "salaryMax": 225000,
  "salaryCurrency": "USD",
  "salaryPeriod": "year",
  "salaryIsEstimate": false,
  "applicants": 25,
  "applicantsRaw": "Be among the first 25 applicants",
  "benefits": ["Dental", "Vision", "Wellness"],
  "companyLinkedInUrl": "https://www.linkedin.com/company/affirm?trk=public_jobs_topcard_logo",
  "companySlug": "affirm",
  "descriptionText": "At Affirm, we exist for the moments that matter...",
  "descriptionLength": 4785,
  "skills": ["Python", "Kotlin", "AWS", "Kubernetes", "MySQL", "REST"],
  "workType": "Remote",
  "experienceLevel": "Mid-Senior level",
  "employmentType": "Full-time",
  "jobFunction": "Engineering and Information Technology",
  "industries": "Financial Services",
  "searchQuery": "software engineer United States",
  "scrapedAt": "2026-09-24T22:56:22.213Z"
}
```

### What you can do with LinkedIn data

**📊 Monitor hiring trends.**

A market analyst runs the scraper weekly for 'data engineer' in 'United States' to track demand shifts and salary floors by region.

**🎯 Build a niche job board.**

A job board operator aggregates remote software roles by running daily scrapes for multiple tech titles and keeping the rows where `workType` is Remote.

**📈 Prospect companies that are growing.**

A sales team scrapes 'sales manager' in their target cities to identify companies with active hiring and reach out with a relevant pitch.

**🧠 Analyze skill requirements.**

An HR analyst extracts skills from 'product manager' postings across several regions to update internal competency models.

### Why choose this scraper

|  | What you get |
|---|---|
| **No login or cookies** | Scrapes public LinkedIn job pages without authentication, so you never risk an account block. |
| **Full detail mode** | Optionally fetches the complete job description, company details, salary, and skills from each listing. |
| **Fast basic mode** | Disable full details to collect job IDs and links only, much faster. In a test on 2026-09-24 basic mode did not fill title, company or location, so keep full details on when you need those. |
| **Rich filters** | Narrow by keyword, location, company ID, date posted, Easy Apply, job type, experience level, workplace type and minimum salary. You pay only for jobs that match. |

### How it compares

This Actor offers full job detail scraping, skill extraction, and raw HTML output alongside the core search, while the alternative focuses on search results with company details.

| Feature | ParseForge | Linkedin Jobs Search |
|---|---|---|
| Full job description scraping | Yes, optional | Not listed |
| Skill extraction from descriptions | Yes, optional | Not listed |
| Raw HTML output | Yes, optional | Not listed |
| Easy Apply filter | Yes | Not listed |
| Salary min and max in every row | Yes | Not listed |
| Workplace type filter (remote, hybrid, on-site) | Yes, checked on each job page | Not listed |
| Company ID filter | Yes | Not listed |

### Configure the run

Drive the Actor from a search query and location. The Input tab lists every parameter. Each example below is ready to paste into the JSON tab of the input.

**1. First run with the defaults.** Returned 8 full jobs in 9.5 seconds on 2026-09-24.

```json
{
  "searchQuery": "software engineer",
  "location": "United States",
  "maxItems": 10
}
```

**2. Jobs posted in the last 24 hours.** Returned 5 jobs, all posted 2026-09-24, in a test on that date.

```json
{
  "searchQuery": "data engineer",
  "location": "United States",
  "maxItems": 50,
  "datePosted": "pastDay"
}
```

**3. Contract jobs only.** Returned 3 jobs on 2026-09-24, all with `employmentType` Contract.

```json
{
  "searchQuery": "contract software developer",
  "location": "United States",
  "maxItems": 50,
  "jobType": ["contract"]
}
```

**4. Remote jobs only.** Returned 3 jobs on 2026-09-24, all with `workType` Remote. The Actor checked 7 jobs and dropped 4.

```json
{
  "searchQuery": "software engineer",
  "location": "United States",
  "maxItems": 50,
  "workplaceType": ["remote"]
}
```

**5. One company's jobs by company ID.** Returned 3 jobs on 2026-09-24, all from Google. To find an ID, filter by company on linkedin.com/jobs and copy the number after `f_C=` in the address bar.

```json
{
  "searchQuery": "software engineer",
  "location": "United States",
  "maxItems": 50,
  "companyId": ["1441"]
}
```

How the filters work: keyword, location, company ID, date posted and Easy Apply are sent to LinkedIn's search. LinkedIn's logged-out search ignores job type, experience level, workplace type, minimum salary and sort order, so the Actor applies those itself after reading each job page. When you filter on a field and a job page does not state it (for example no published salary, or seniority "Not Applicable"), that job is dropped. Dropped jobs are not charged. The run's status message says how many jobs were checked, kept and dropped. If fewer than 3% of the first 100 jobs checked match, the run stops early and says so, so you do not wait on a search that cannot fill your request. Most recent sorting is applied to the final results, which are then written at the end of the run.

### Pricing

Pay per event. You pay only for jobs written to your dataset, plus a small start fee per run.

| Event | Free plan | Top tier |
|---|---|---|
| Job returned | $0.00265 | $0.002359 |
| Run start | $0.001 | $0.00089 |

| Jobs collected | Approximate cost on the free plan |
|---|---|
| 100 jobs | $0.27 |
| 1,000 jobs | $2.65 |
| 10,000 jobs | $26.50 |

New Apify accounts start with $5 in free credit.

### Free users

Free-plan runs return up to 10 results as a preview. [Upgrade your Apify plan](https://console.apify.com/sign-up?fpr=vmoqkp) to collect up to 1,000,000 results per run.

### Run it

1. [Create a free Apify account with $5 in credit](https://console.apify.com/sign-up?fpr=vmoqkp).
2. Open the [LinkedIn Jobs Scraper](https://apify.com/parseforge/linkedin-jobs-scraper?fpr=vmoqkp).
3. Set your inputs and any filters, then click **Start**.
4. Export the results as CSV, Excel, JSON, or XML from the **Dataset** tab.

Run it programmatically through the [Apify API](https://docs.apify.com/api/v2) (`run-sync-get-dataset-items`) or the [ApifyClient](https://docs.apify.com/api/client/js) for JavaScript and Python.

### Use with AI agents (MCP)

Give an AI agent live access to LinkedIn through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

```bash
claude mcp add --transport http apify "https://mcp.apify.com?tools=parseforge/linkedin-jobs-scraper"
```

Then prompt it in plain language to run the scraper and read back the results.

### Troubleshooting

**Why am I getting no results?**

Check that your search query and location combination returns results on LinkedIn.com. Try broadening the location or removing restrictive filters like Easy Apply or a high minimum salary. A run that ends with 0 jobs is marked Failed, and its status message and log say why, including how many jobs each filter dropped.

**Why are some jobs missing full details?**

Some LinkedIn job postings block detail access. Enable 'Include Blocked Jobs' to still receive basic info for those listings with an isBlocked=true flag.

**The scraper is running slowly. How can I speed it up?**

Increase max concurrency, though this may raise the chance of blocks. Disabling 'Scrape Full Job Details' is faster but currently returns only job IDs and links.

**I'm getting blocked or seeing empty results after many runs.**

Reduce the max concurrency setting to a lower number, such as 5, to make requests less aggressive and avoid triggering LinkedIn's rate limits.

### FAQ

| Question | Answer |
|---|---|
| Do I need a LinkedIn account or API key to use this? | No. The scraper reads public LinkedIn job search pages and requires no login, cookies, or API credentials. |
| Can I scrape jobs from a specific company? | Yes, with Company ID. A company name in the search query is only a keyword and returns other employers too. Put the LinkedIn company ID in `companyId` instead: a test with `1441` returned only Google jobs. |
| How many jobs can I collect in one run? | You can set the maximum up to 1,000,000 jobs. The actual number returned depends on how many match your search and filters. |
| Will I get the same job twice in one run? | No. Each LinkedIn job ID is written once per run. A company that posts the same role in several cities has a separate job ID per city, so those appear as separate rows. |
| What is the difference between basic and full detail mode? | Full detail mode, the default, opens every job page and fills all 31 fields. Basic mode skips the job pages and currently returns the job ID and link only. |
| Can I filter by remote jobs only? | Yes. Set the workplace type filter to 'Remote'. The Actor reads the workplace wording on each job page and keeps only jobs that say remote; jobs with no workplace wording are dropped and not charged. |
| Does this scraper handle LinkedIn's anti-scraping measures? | The Actor runs on Apify's infrastructure with rotating proxies and configurable concurrency. Lower the max concurrency if you encounter blocks. |
| Can I get the raw HTML of each job page? | Yes. Enable the 'Include Raw HTML' option to receive the full HTML of each job detail page in your output for custom parsing. |
| How do I extract skills from job descriptions? | Enable the 'Extract Skills' option. The scraper will parse the job description and return a list of skills mentioned. |
| What export formats are supported? | You can export your dataset to CSV, JSON, Excel, or XML from the Apify platform. |
| Can I schedule this scraper to run daily? | Yes. Use Apify's scheduler to run the Actor at any interval, such as hourly or daily, to track new postings over time. |

### Related actors

Browse the full [ParseForge collection](https://apify.com/parseforge?fpr=vmoqkp) for more scrapers.

🆘 **Need help?** Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ **Disclaimer.** This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by LinkedIn Corporation. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.

# Actor input Schema

## `searchQuery` (type: `string`):

Job title or keywords to search for. A company name here is treated as a keyword; use Company ID to get one company's jobs only.

## `location` (type: `string`):

City, state, country, or 'Remote'

## `companyId` (type: `array`):

LinkedIn numeric company IDs. Returns only jobs posted by these companies. To find an ID, filter by company on linkedin.com/jobs and copy the number after f_C= in the address bar, for example 1441 for Google. Can be combined with a search query.

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

How many jobs to collect per run.

## `datePosted` (type: `string`):

Filter jobs by when they were posted

## `jobType` (type: `array`):

Keep only these employment types. Applied by the Actor after it reads each job page (LinkedIn's logged-out search ignores this filter). Jobs whose page does not state an employment type are dropped when this is set.

## `experienceLevel` (type: `array`):

Keep only these seniority levels. Applied by the Actor after it reads each job page (LinkedIn's logged-out search ignores this filter). Jobs listed as 'Not Applicable' or with no level are dropped when this is set.

## `workplaceType` (type: `array`):

Keep only on-site, remote or hybrid jobs. Applied by the Actor after it reads each job page, using the workplace wording on the page (LinkedIn's logged-out search ignores this filter). Jobs with no workplace wording are dropped when this is set.

## `easyApplyOnly` (type: `boolean`):

Only return jobs with LinkedIn Easy Apply

## `salary` (type: `string`):

Keep only jobs whose published USD salary (lower end of the range, hourly and monthly pay converted to yearly) is at least this amount. Applied by the Actor after it reads each job page. Jobs with no published USD salary are dropped when this is set.

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

Most recent sorts the final results by posted date, newest first. The Actor does this itself, because LinkedIn's logged-out search ignores the sort order. With Most recent, results are written at the end of the run.

## `scrapeJobDetails` (type: `boolean`):

Open each job page to fill all 31 fields: description, salary, skills, seniority, employment type, company details. Keep this on. When off, the run skips the job pages and currently returns only the job ID and link for each job. It is turned on automatically when you use the job type, experience, workplace or salary filters.

## `extractSkills` (type: `boolean`):

Parse skills from job descriptions

## `includeBlockedJobs` (type: `boolean`):

Include jobs where full details could not be retrieved. Returns basic info with isBlocked=true flag.

## `includeRawHtml` (type: `boolean`):

Include the raw HTML of the job detail page in the output for custom parsing.

## `maxConcurrency` (type: `integer`):

Maximum number of parallel requests. Lower if you experience blocks.

## Actor input object example

```json
{
  "searchQuery": "software engineer",
  "location": "United States",
  "maxItems": 10,
  "datePosted": "anyTime",
  "jobType": [],
  "experienceLevel": [],
  "workplaceType": [],
  "easyApplyOnly": false,
  "sortBy": "relevant",
  "scrapeJobDetails": true,
  "extractSkills": true,
  "maxConcurrency": 10
}
```

# Actor output Schema

## `jobs` (type: `string`):

Complete dataset with all scraped job listings including full details

## `overview` (type: `string`):

Summary view with key job fields in a table format

# 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 = {
    "searchQuery": "software engineer",
    "location": "United States",
    "maxItems": 10,
    "scrapeJobDetails": true,
    "extractSkills": true,
    "includeBlockedJobs": false,
    "includeRawHtml": false,
    "maxConcurrency": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("parseforge/linkedin-jobs-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 = {
    "searchQuery": "software engineer",
    "location": "United States",
    "maxItems": 10,
    "scrapeJobDetails": True,
    "extractSkills": True,
    "includeBlockedJobs": False,
    "includeRawHtml": False,
    "maxConcurrency": 10,
}

# Run the Actor and wait for it to finish
run = client.actor("parseforge/linkedin-jobs-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 '{
  "searchQuery": "software engineer",
  "location": "United States",
  "maxItems": 10,
  "scrapeJobDetails": true,
  "extractSkills": true,
  "includeBlockedJobs": false,
  "includeRawHtml": false,
  "maxConcurrency": 10
}' |
apify call parseforge/linkedin-jobs-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,parseforge/linkedin-jobs-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/0lLu3ht7kPSG6K7qi/builds/XdA0yohFJD3h6bzAC/openapi.json