# LinkedIn Job Scraper π° $0.27/1K (`blackfalcondata/linkedin-job-scraper`) Actor
Scrape LinkedIn job postings with full descriptions, salary, skills, and employer details (company size, website, industry) β no login or cookies. Clean structured output for hiring research, lead generation, and job aggregation. Incremental mode optionally skips already-seen jobs on recurring runs.
- **URL**: https://apify.com/blackfalcondata/linkedin-job-scraper.md
- **Developed by:** [Black Falcon Data](https://apify.com/blackfalcondata) (community)
- **Categories:** Jobs, Lead generation, Automation
- **Stats:** 23 total users, 6 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: 5.00 out of 5 stars
## Pricing
from $1.00 / 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/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
Actors are written with capital "A".
## 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.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).
For usage examples, see the [API](#api) section below.
For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
# README
### What does LinkedIn Job Scraper do?
LinkedIn Job Scraper extracts [linkedin.com](https://linkedin.com) job postings β full descriptions, salary, skills, apply URLs, AI-ready summaries, and employer details (company size, website, industry) β with no login or cookies, at $0.27 per 1,000 results. Run a one-off export, or enable incremental mode to skip already-seen jobs on recurring runs.
**New to Apify?** [Sign up free](https://console.apify.com/sign-up?fpr=1h3gvi) and use the included $5 monthly platform credit to test this actor.
### Key features
- **β»οΈ Incremental mode** β recurring runs emit only NEW / UPDATED / REAPPEARED records; UNCHANGED and EXPIRED are opt-in. First run builds the baseline; subsequent runs emit and charge only for the diff.
- **π Notifications** β Telegram, Slack, Discord, WhatsApp Cloud API, and generic webhook outputs. Pair with incremental + `notifyOnlyChanges` for daily new-job alerts.
- **π€ AI-ready output** β deterministic `aiSummary` and `skills` fields give compact context for ATS, recruiting agents, and MCP workflows without extra enrichment calls.
- **π Paste-mode** β paste a LinkedIn job search URL copied from your browser. The actor reads the URL's keywords, location, geoId, date, work type, job type, company, Easy Apply, and sort filters and runs that search directly.
- **π« Recruiter-spam filter** β `removeAgency: true` runs a heuristic post-filter on company names and drops listings from third-party agencies.
- **π Detail enrichment** β two-stage mode: list, then enrich each job with the full description plus detail-page fields such as apply counts and education.
- **βοΈ Description truncation** β cap enriched descriptions with `descriptionMaxLength` when downstream systems need smaller records.
- **π Multi-region with presets** β pass `regions: ["US", "GB", "DE"]` for a custom country mix, or pick presets like `"nordic"`, `"dach"`, `"benelux"`, `"uk-ireland"`, `"eu-27"`, `"gcc"`, `"mena"`, `"asean"`, `"latam"`, or `"anglosphere"`.
- **β‘ Easy-Apply filter** β `easyApply: true` returns only LinkedIn Easy-Apply postings.
- **π’ Company-level filtering** β `companies: [123, 456]` filters at the LinkedIn API level, while `excludeCompanies` and `excludeKeywords` remove unwanted matches after fetch.
- **π¦ Compact mode** β AI-agent and MCP-friendly compact payloads with core fields only; pipe them into your ATS, monitoring workflow, or LLM context without parsing extras.
### What data can you extract from linkedin.com?
Each result includes Core listing fields (`scrapedAt`, `portalUrl`, `jobId`, `linkedinJobId`, `jobUrl`, `title`, `location`, and `country`, and more), detail fields when enrichment is enabled (`description`, `descriptionHtml`, `descriptionMarkdown`, and `postingBenefits`), apply information (`applyUrl`, `applyType`, and `easyApply`), and company metadata (`company`, `companyUrl`, `companyId`, and `companyLogo`). In standard mode, all fields are always present β unavailable data points are returned as `null`, never omitted. In compact mode, only core fields are returned.
### Input
The main inputs are an optional location filter and a result limit. Additional filters and options are available in the input schema.
Key parameters:
- **`keywords`** β Job search keywords (e.g. "software engineer", "nurse"). Leave blank to browse all jobs in the selected location.
- **`location`** β City, state, region, or country (e.g. "Berlin, Germany", "United States"). LinkedIn resolves it for you β no IDs needed. Leave empty for global results.
- **`geoIds`** β Advanced/optional override β most users just use π Location, which LinkedIn resolves automatically. For exact targeting, paste a LinkedIn jobs search URL into π Start URLs (the geoId is read for you), or copy the numeric geoId from a LinkedIn jobs URL. Each geoId becomes a separate query, deduped on jobId. (default: `[]`)
- **`regions`** β Two-letter country codes (e.g. "US", "GB", "DE"). Resolved to LinkedIn country geoIds. Use geoIds[] for unsupported markets. (default: `[]`)
- **`regionPresets`** β Pre-defined country grouping. Combined with regions[] if both are set.
- **`datePosted`** β Filter by posting recency. "lastHour" is unique to this scraper. (default: `"anytime"`)
- **`jobType`** β Multi-select employment type filter. (default: `[]`)
- **`experienceLevel`** β Multi-select seniority filter. (default: `[]`)
- **`workType`** β Multi-select onsite/remote/hybrid filter. (default: `[]`)
- **`salaryMin`** β Minimum annual salary (USD). Mapped to LinkedIn's nearest f_SB2 bucket. Post-filtered exactly.
- **`salaryMax`** β Maximum annual salary. Post-filtered (LinkedIn has no native max filter).
- **`salaryIncludeUnknown`** β When salaryMin/Max set, include jobs with no salary data. (default: `true`)
- ...and 38 more parameters
### Input examples
**Basic search** β Keyword-driven search with a result cap.
β Full payload per result β all standard fields populated where the source provides them.
```json
{
"keywords": "software engineer",
"maxResults": 50
}
````
**Filtered search** β Narrow results with advanced filters β only matching jobs are returned.
β Same field set as basic search; fewer, more relevant rows.
```json
{
"keywords": "software engineer",
"jobType": [
"fulltime"
],
"workType": [
"onsite"
],
"experienceLevel": [
"internship"
],
"maxResults": 100
}
```
**Incremental tracking** β Only emit jobs that changed since the previous run with this `stateKey`.
β First run builds the baseline state. Subsequent runs emit only records that are new or whose tracked content changed. Set `emitUnchanged: true` to include unchanged records as well.
```json
{
"keywords": "software engineer",
"maxResults": 200,
"incrementalMode": true,
"stateKey": "software-engineer-tracker"
}
```
**Compact filtered output** β Combine filters with compact mode for a lightweight AI-agent or MCP data source.
β Core fields only β ideal for piping into LLMs or downstream tools without token overhead.
```json
{
"keywords": "software engineer",
"jobType": [
"fulltime"
],
"workType": [
"onsite"
],
"maxResults": 50,
"compact": true
}
```
### Output
Each run produces a dataset of structured job records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console.
### Example job record
```json
{
"scrapedAt": "2026-04-27T19:02:37.769Z",
"portalUrl": "https://www.linkedin.com",
"source": "linkedin",
"jobId": "1705fc4ee704bf3584cf2654b20e8f95383167563ff7ecd0184b58d2c7d66236",
"linkedinJobId": "4406118990",
"jobUrl": "https://www.linkedin.com/jobs/view/software-engineer-new-grad-at-notion-4406118990",
"title": "Software Engineer, New Grad",
"company": "Notion",
"companyUrl": "https://www.linkedin.com/company/notionhq",
"companyId": "notionhq",
"location": "San Francisco, CA",
"country": "CA",
"postedAt": "2026-04-24T00:00:00.000Z",
"applyUrl": "https://www.linkedin.com/jobs/view/software-engineer-new-grad-at-notion-4406118990",
"applyType": "unknown",
"description": "About Us Notion helps you build beautiful tools for your lifeβs work. In today's world of endless apps and tabs, Notion provides one place for teams to get everything done, seamlessly connecting docs,...",
"descriptionHtml": "About Us
Notion helps you build beautiful tools for your lifeβs work. In today's world of endless apps and tabs, Notion provides one place for teams to get everything done, sea...",
"descriptionMarkdown": "About Us Notion helps you build beautiful tools for your lifeβs work. In today's world of endless apps and tabs, Notion provides one place for teams to get everything done, seamlessly connecting docs,...",
"seniorityLevel": "Not Applicable",
"employmentType": "Full-time",
"industry": "Software Development",
"jobFunction": "Engineering and Information Technology",
"workplaceType": null,
"applicantCount": 200,
"easyApply": false,
"salaryMin": null,
"salaryMax": null,
"salaryCurrency": null,
"salaryPeriod": null,
"salarySource": null,
"salaryIsPredicted": null,
"companyLogo": null,
"companyDescription": null,
"companyEmployeeCount": null,
"companyWebsite": null,
"companyAddress": null,
"recruiterName": null,
"recruiterUrl": null,
"recruiterTitle": null,
"extractedEmails": [],
"extractedPhones": [],
"extractedUrls": [],
"socialProfiles": {
"linkedin": [],
"twitter": [],
"instagram": [],
"facebook": [],
"youtube": [],
"tiktok": [],
"github": [],
"xing": []
},
"changeType": null,
"firstSeenAt": null,
"lastSeenAt": null,
"previousSeenAt": null,
"expiredAt": null,
"isRepost": null,
"repostOfId": null,
"repostDetectedAt": null,
"language": null,
"contentHash": "eda6ea0d0ad7711b94b796376d0ace88eaf03a62afdefe9708fa4f1c7ae4ae8f",
"isPromoted": false,
"postingBenefits": [
"Actively Hiring"
],
"trackingId": "U6ZtuvNYKrwizG8bYR1Kqw=="
}
```
### Incremental fields
When `incremental: true`, each record also carries:
- `changeType` β one of `NEW`, `UPDATED`, `UNCHANGED`, `REAPPEARED`, `EXPIRED`. Default output covers `NEW` / `UPDATED` / `REAPPEARED`; set `emitUnchanged: true` or `emitExpired: true` to opt into the others.
- `firstSeenAt`, `lastSeenAt` β ISO-8601 timestamps tracking the listing across runs.
- `isRepost`, `repostOfId`, `repostDetectedAt` β populated when a new listing matches the tracked content of a previously expired one. Set `skipReposts: true` to drop detected reposts from the output.
### How to scrape linkedin.com
1. Go to [LinkedIn Job Scraper](https://apify.com/blackfalcondata/linkedin-job-scraper?fpr=1h3gvi) in Apify Console.
2. Configure the input and optional location filter.
3. Set `maxResults` to control how many results you need.
4. Click **Start** and wait for the run to finish.
5. Export the dataset as JSON, CSV, or Excel.
### Use cases
- Extract job data from linkedin.com for market research and competitive analysis.
- Monitor hiring demand across regions and categories over time.
- Monitor new and changed listings on scheduled runs without processing the full dataset every time.
- Auto-apply or feed apply URLs into your ATS / hiring pipeline.
- Research company hiring patterns, employer profiles, and industry distribution.
- Use structured location data for regional analysis, mapping, and geo-targeting.
- Feed structured data into AI agents, MCP tools, and automated pipelines using compact mode.
- Export clean, structured data to dashboards, spreadsheets, or data warehouses.
### How much does it cost to scrape linkedin.com?
LinkedIn Job Scraper uses [pay-per-event](https://docs.apify.com/platform/actors/paid-actors/pay-per-event) pricing. You pay a small fee when the run starts and then for each result that is actually produced.
- **Run start:** $0.0005 per run
- **Per result:** $0.00027 per job record
Example costs:
- 10 results: **$0.0032**
- 25 results: **$0.00725**
- 100 results: **$0.03**
- 200 results: **$0.05**
- 500 results: **$0.14**
#### Example: recurring monitoring savings
These examples compare full re-scrapes with incremental runs at different churn rates. Churn is the share of listings that are new or whose tracked content changed since the previous run. Actual churn depends on your query breadth, source activity, and polling frequency β the scenarios below are examples, not predictions.
Example setup: 250 results per run, daily polling (30 runs/month). Event-pricing examples scale linearly with result count.
| Churn rate | Full re-scrape run cost | Incremental run cost | Savings vs full re-scrape | Monthly cost after baseline |
|---|---:|---:|---:|---:|
| 5% β stable niche query | $0.07 | $0.00387 | $0.06 (94%) | $0.12 |
| 15% β moderate broad query | $0.07 | $0.01 | $0.06 (84%) | $0.32 |
| 30% β high-volume aggregator | $0.07 | $0.02 | $0.05 (69%) | $0.62 |
Full re-scrape monthly cost at daily polling: $2.04. First month with incremental costs $0.18 / $0.38 / $0.67 for the 5% / 15% / 30% scenarios because the first run builds baseline state at full cost before incremental savings apply.
### FAQ
#### How many results can I get from linkedin.com?
The number of results depends on the search query and available listings on linkedin.com. Use the `maxResults` parameter to control how many results are returned per run.
#### Does LinkedIn Job Scraper support recurring monitoring?
Yes. Enable incremental mode to only receive new or changed listings on subsequent runs. This is ideal for scheduled monitoring where you want to track changes over time without re-processing the full dataset.
#### Can I integrate LinkedIn Job Scraper with other apps?
Yes. LinkedIn Job Scraper works with Apify's [integrations](https://apify.com/integrations?fpr=1h3gvi) to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes.
#### Can I use LinkedIn Job Scraper with the Apify API?
Yes. You can start runs, manage inputs, and retrieve results programmatically through the [Apify API](https://docs.apify.com/api/v2). Client libraries are available for JavaScript, Python, and other languages.
#### Can I use LinkedIn Job Scraper through an MCP Server?
Yes. Apify provides an [MCP Server](https://apify.com/apify/actors-mcp-server?fpr=1h3gvi) that lets AI assistants and agents call this actor directly. Use compact mode and `descriptionMaxLength` to keep payloads manageable for LLM context windows.
#### Is it legal to scrape linkedin.com?
This actor extracts publicly available data from linkedin.com. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant.
#### Your feedback
If you have questions, need a feature, or found a bug, please [open an issue](https://apify.com/blackfalcondata/linkedin-job-scraper/issues?fpr=1h3gvi) on the actor's page in Apify Console. Your feedback helps us improve.
### You might also like
- [Actiris Brussels Job Scraper](https://apify.com/blackfalcondata/actiris-scraper?fpr=1h3gvi) β Scrape all active job listings from actiris.brussels β official Brussels public employment service..
- [Adzuna Job Scraper β Global Jobs with Salary & Coordinates](https://apify.com/blackfalcondata/adzuna-scraper?fpr=1h3gvi) β Scrape adzuna.com job listings across 19 country markets with structured salary data.
- [APEC.fr Scraper - French Executive Jobs](https://apify.com/blackfalcondata/apec-scraper?fpr=1h3gvi) β Scrape apec.fr - French executive job listings with salary ranges, company, location, skills,.
- [Arbeitsagentur Jobs Feed β German Federal Employment Agency](https://apify.com/blackfalcondata/arbeitsagentur-jobs-feed?fpr=1h3gvi) β Extract job listings from arbeitsagentur.de β Germany's official public employment portal with 1M+.
- [Arbeitsagentur Scraper - German Jobs](https://apify.com/blackfalcondata/arbeitsagentur-scraper?fpr=1h3gvi) β Scrape arbeitsagentur.de - Germanyβs official employment portal with 1M+ listings. Contact data,.
- [Arbetsformedlingen Job Scraper](https://apify.com/blackfalcondata/arbetsformedlingen-scraper?fpr=1h3gvi) β Scrape arbetsformedlingen.se (Platsbanken) β Sweden's official employment portal. Returns 84.
- [AutoScout24 Scraper β European Car Listings with Dealer Data](https://apify.com/blackfalcondata/autoscout24-scraper?fpr=1h3gvi) β Scrape autoscout24.com - Europe's largest used car marketplace with 770K+ listings. Structured.
- [Bayt.com Scraper β MENA Jobs with Salary & Skills Filter](https://apify.com/blackfalcondata/bayt-scraper?fpr=1h3gvi) β Scrape bayt.com β leading Middle East job board covering UAE, Saudi Arabia, Qatar, Egypt and 9 more.
### Getting started with Apify
New to Apify? [Create a free account with $5 credit](https://console.apify.com/sign-up?fpr=1h3gvi) β no credit card required.
1. Sign up β $5 platform credit included
2. Open this actor and configure your input
3. Click **Start** β export results as JSON, CSV, or Excel
Need more later? [See Apify pricing](https://apify.com/pricing?fpr=1h3gvi).
# Actor input Schema
## `keywords` (type: `string`):
Job search keywords (e.g. "software engineer", "nurse"). Leave blank to browse all jobs in the selected location.
## `location` (type: `string`):
City, state, region, or country (e.g. "Berlin, Germany", "United States"). LinkedIn resolves it for you β no IDs needed. Leave empty for global results.
## `geoIds` (type: `array`):
Advanced/optional override β most users just use π Location, which LinkedIn resolves automatically. For exact targeting, paste a LinkedIn jobs search URL into π Start URLs (the geoId is read for you), or copy the numeric geoId from a LinkedIn jobs URL. Each geoId becomes a separate query, deduped on jobId.
## `regions` (type: `array`):
Two-letter country codes (e.g. "US", "GB", "DE"). Resolved to LinkedIn country geoIds. Use geoIds\[] for unsupported markets.
## `regionPresets` (type: `string`):
Pre-defined country grouping. Combined with regions\[] if both are set.
## `datePosted` (type: `string`):
Filter by posting recency. "lastHour" is unique to this scraper.
## `jobType` (type: `array`):
Multi-select employment type filter.
## `experienceLevel` (type: `array`):
Multi-select seniority filter.
## `workType` (type: `array`):
Multi-select onsite/remote/hybrid filter.
## `salaryMin` (type: `integer`):
Minimum annual salary (USD). Mapped to LinkedIn's nearest f\_SB2 bucket. Post-filtered exactly.
## `salaryMax` (type: `integer`):
Maximum annual salary. Post-filtered (LinkedIn has no native max filter).
## `salaryIncludeUnknown` (type: `boolean`):
When salaryMin/Max set, include jobs with no salary data.
## `companies` (type: `array`):
Numeric LinkedIn companyIds (filter at API level).
## `excludeCompanies` (type: `array`):
Company-name substrings to exclude (case-insensitive post-filter).
## `excludeKeywords` (type: `array`):
Title substrings to exclude (case-insensitive post-filter).
## `easyApply` (type: `boolean`):
Restrict results to LinkedIn Easy Apply postings.
## `removeAgency` (type: `boolean`):
Heuristic post-filter on company name ("recruitment", "staffing", etc.).
## `distance` (type: `integer`):
Search radius around location. LinkedIn auto-detects unit (miles in US/UK/CA/AU/NZ; km elsewhere).
## `sortBy` (type: `string`):
Sort order. "recent" is recommended for incremental feeds.
## `startUrls` (type: `array`):
LinkedIn job search URLs copied from the browser. Search filters from the URL are used as the query.
## `proxyConfiguration` (type: `object`):
Network egress configuration. Use the default unless you need a custom proxy setup.
## `linkedinHost` (type: `string`):
Subdomain (e.g. "www", "de"). Affects default geo-routing + UI labels.
## `outputLanguage` (type: `string`):
HTTP Accept-Language header. Default en-US for parsing-cleanliness.
## `incrementalMode` (type: `boolean`):
Persist seen-jobIds across runs; emit only NEW + UPDATED. Requires stateKey.
## `stateKey` (type: `string`):
Optional stable identifier for the tracked search universe. Leave empty to auto-derive a stable identifier from your search inputs β different keyword/location/filter combinations get isolated state automatically.
## `allowNonIncrementalFallback` (type: `boolean`):
If incremental mode is requested but the state store is not accessible on this account, fall back to a non-incremental run instead of failing. Default: fail loudly so missing state is not silently ignored.
## `outputMode` (type: `string`):
Which items to emit when in incrementalMode.
## `emitUnchanged` (type: `boolean`):
Include items that haven't changed since last run.
## `emitExpired` (type: `boolean`):
Include items that disappeared from search results.
## `skipReposts` (type: `boolean`):
Suppress jobs with the same content as a previously-seen but inactive listing.
## `enrichDetails` (type: `boolean`):
Fetch each job's detail page for full description, seniorityLevel, employmentType, jobFunction, industry, and applicantCount. Adds 1 HTTP request per job.
## `scrapeCompany` (type: `boolean`):
For each job, fetch the employer's public LinkedIn company page and add company description, website, employee count, logo, and address. Fetched once per unique company.
## `discoverRelated` (type: `boolean`):
After the main SERP, fetch LinkedIn's relatedJobs feed for the first N results to discover jobs that don't surface on the keyword search. Useful for thin markets.
## `relatedSeedCount` (type: `integer`):
How many of the first SERP results are used as seeds for relatedJobs expansion. Each seed yields up to 10 candidates.
## `telegramToken` (type: `string`):
Bot token from @BotFather. Leave empty to disable Telegram notifications.
## `telegramChatId` (type: `string`):
Numeric chat or channel ID where notifications should be sent.
## `discordWebhookUrl` (type: `string`):
Channel webhook URL. Leave empty to disable Discord notifications.
## `slackWebhookUrl` (type: `string`):
Incoming webhook URL. Leave empty to disable Slack notifications.
## `whatsappAccessToken` (type: `string`):
Permanent System User token from Meta Business.
## `whatsappPhoneNumberId` (type: `string`):
Numeric phone-number ID from the Meta dashboard.
## `whatsappTo` (type: `string`):
Recipient phone number in E.164 format (e.g. "4561234567").
## `webhookUrl` (type: `string`):
Receives a JSON POST of {metadata, items} for each batch.
## `webhookHeaders` (type: `object`):
Additional HTTP headers to include with the generic webhook (e.g. Authorization).
## `notificationLimit` (type: `integer`):
Cap on items included in each notification message.
## `notifyOnlyChanges` (type: `boolean`):
When in incrementalMode, suppress notifications for UNCHANGED items.
## `compact` (type: `boolean`):
Emit only core fields (keeps cost the same; reduces dataset size).
## `descriptionMaxLength` (type: `integer`):
Truncate description (0 = no truncation). Only relevant when enrichDetails=true.
## `phoneExtractionMode` (type: `string`):
"strict" requires Tel:/+CC prefix; "lenient" also picks up bare local-format numbers.
## `maxResults` (type: `integer`):
Cap on emitted items (0 = unlimited).
## `descriptionFormat` (type: `string`):
Pick a single description representation. `all` keeps every variant; `text` / `html` / `markdown` drop the others.
## `excludeEmptyFields` (type: `boolean`):
Drop null, empty-string, and empty-array fields from each record before push. Smaller payloads for AI agents and dashboards.
## Actor input object example
```json
{
"keywords": "software engineer",
"geoIds": [],
"regions": [],
"datePosted": "anytime",
"jobType": [],
"experienceLevel": [],
"workType": [],
"salaryIncludeUnknown": true,
"companies": [],
"excludeCompanies": [],
"excludeKeywords": [],
"easyApply": false,
"removeAgency": false,
"sortBy": "recent",
"startUrls": [],
"proxyConfiguration": {
"useApifyProxy": true
},
"linkedinHost": "www",
"outputLanguage": "en-US,en;q=0.9",
"incrementalMode": false,
"allowNonIncrementalFallback": false,
"outputMode": "all",
"emitUnchanged": false,
"emitExpired": false,
"skipReposts": false,
"enrichDetails": false,
"scrapeCompany": false,
"discoverRelated": false,
"relatedSeedCount": 5,
"notificationLimit": 5,
"notifyOnlyChanges": false,
"compact": false,
"descriptionMaxLength": 0,
"phoneExtractionMode": "strict",
"maxResults": 100,
"descriptionFormat": "all",
"excludeEmptyFields": false
}
```
# Actor output Schema
## `results` (type: `string`):
No description
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"keywords": "software engineer",
"easyApply": false,
"removeAgency": false,
"incrementalMode": false,
"enrichDetails": false,
"scrapeCompany": false,
"discoverRelated": false,
"compact": false,
"descriptionFormat": "all",
"excludeEmptyFields": false
};
// Run the Actor and wait for it to finish
const run = await client.actor("blackfalcondata/linkedin-job-scraper").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`πΎ 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);
});
// π Want to learn more π? Go to β 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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"keywords": "software engineer",
"easyApply": False,
"removeAgency": False,
"incrementalMode": False,
"enrichDetails": False,
"scrapeCompany": False,
"discoverRelated": False,
"compact": False,
"descriptionFormat": "all",
"excludeEmptyFields": False,
}
# Run the Actor and wait for it to finish
run = client.actor("blackfalcondata/linkedin-job-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("πΎ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# π Want to learn more π? Go to β https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"keywords": "software engineer",
"easyApply": false,
"removeAgency": false,
"incrementalMode": false,
"enrichDetails": false,
"scrapeCompany": false,
"discoverRelated": false,
"compact": false,
"descriptionFormat": "all",
"excludeEmptyFields": false
}' |
apify call blackfalcondata/linkedin-job-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=blackfalcondata/linkedin-job-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "LinkedIn Job Scraper π° $0.27/1K",
"description": "Scrape LinkedIn job postings with full descriptions, salary, skills, and employer details (company size, website, industry) β no login or cookies. Clean structured output for hiring research, lead generation, and job aggregation. Incremental mode optionally skips already-seen jobs on recurring runs.",
"version": "0.1",
"x-build-id": "lYfT4LsTZwE0MzB5V"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/blackfalcondata~linkedin-job-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-blackfalcondata-linkedin-job-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/blackfalcondata~linkedin-job-scraper/runs": {
"post": {
"operationId": "runs-sync-blackfalcondata-linkedin-job-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/blackfalcondata~linkedin-job-scraper/run-sync": {
"post": {
"operationId": "run-sync-blackfalcondata-linkedin-job-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"keywords": {
"title": "π Search keywords",
"type": "string",
"description": "Job search keywords (e.g. \"software engineer\", \"nurse\"). Leave blank to browse all jobs in the selected location."
},
"location": {
"title": "π Location",
"type": "string",
"description": "City, state, region, or country (e.g. \"Berlin, Germany\", \"United States\"). LinkedIn resolves it for you β no IDs needed. Leave empty for global results."
},
"geoIds": {
"title": "π LinkedIn geoId (advanced)",
"type": "array",
"description": "Advanced/optional override β most users just use π Location, which LinkedIn resolves automatically. For exact targeting, paste a LinkedIn jobs search URL into π Start URLs (the geoId is read for you), or copy the numeric geoId from a LinkedIn jobs URL. Each geoId becomes a separate query, deduped on jobId.",
"default": [],
"items": {
"type": "string"
}
},
"regions": {
"title": "πΊ ISO-2 region codes",
"type": "array",
"description": "Two-letter country codes (e.g. \"US\", \"GB\", \"DE\"). Resolved to LinkedIn country geoIds. Use geoIds[] for unsupported markets.",
"default": [],
"items": {
"type": "string"
}
},
"regionPresets": {
"title": "π Region preset",
"enum": [
"nordic",
"dach",
"benelux",
"uk-ireland",
"eu-27",
"gcc",
"mena",
"asean",
"anglosphere",
"latam",
"nordics-extended"
],
"type": "string",
"description": "Pre-defined country grouping. Combined with regions[] if both are set."
},
"datePosted": {
"title": "π Date posted",
"enum": [
"anytime",
"lastHour",
"last24h",
"last7d",
"last30d"
],
"type": "string",
"description": "Filter by posting recency. \"lastHour\" is unique to this scraper.",
"default": "anytime"
},
"jobType": {
"title": "πΌ Job type",
"type": "array",
"description": "Multi-select employment type filter.",
"items": {
"type": "string",
"enum": [
"fulltime",
"parttime",
"contract",
"temporary",
"internship",
"volunteer",
"other"
]
},
"default": []
},
"experienceLevel": {
"title": "π Experience level",
"type": "array",
"description": "Multi-select seniority filter.",
"items": {
"type": "string",
"enum": [
"internship",
"entry",
"associate",
"mid_senior",
"director",
"executive"
]
},
"default": []
},
"workType": {
"title": "π Work type",
"type": "array",
"description": "Multi-select onsite/remote/hybrid filter.",
"items": {
"type": "string",
"enum": [
"onsite",
"remote",
"hybrid"
]
},
"default": []
},
"salaryMin": {
"title": "π° Salary min",
"minimum": 0,
"type": "integer",
"description": "Minimum annual salary (USD). Mapped to LinkedIn's nearest f_SB2 bucket. Post-filtered exactly."
},
"salaryMax": {
"title": "π° Salary max",
"minimum": 0,
"type": "integer",
"description": "Maximum annual salary. Post-filtered (LinkedIn has no native max filter)."
},
"salaryIncludeUnknown": {
"title": "Include jobs without salary",
"type": "boolean",
"description": "When salaryMin/Max set, include jobs with no salary data.",
"default": true
},
"companies": {
"title": "π’ Company IDs to include",
"type": "array",
"description": "Numeric LinkedIn companyIds (filter at API level).",
"default": [],
"items": {
"type": "string"
}
},
"excludeCompanies": {
"title": "π« Exclude companies",
"type": "array",
"description": "Company-name substrings to exclude (case-insensitive post-filter).",
"default": [],
"items": {
"type": "string"
}
},
"excludeKeywords": {
"title": "π« Exclude keywords",
"type": "array",
"description": "Title substrings to exclude (case-insensitive post-filter).",
"default": [],
"items": {
"type": "string"
}
},
"easyApply": {
"title": "β‘ Easy Apply only",
"type": "boolean",
"description": "Restrict results to LinkedIn Easy Apply postings.",
"default": false
},
"removeAgency": {
"title": "π« Remove staffing agencies",
"type": "boolean",
"description": "Heuristic post-filter on company name (\"recruitment\", \"staffing\", etc.).",
"default": false
},
"distance": {
"title": "π Distance (km/mi)",
"minimum": 0,
"type": "integer",
"description": "Search radius around location. LinkedIn auto-detects unit (miles in US/UK/CA/AU/NZ; km elsewhere)."
},
"sortBy": {
"title": "π Sort",
"enum": [
"recent",
"relevant"
],
"type": "string",
"description": "Sort order. \"recent\" is recommended for incremental feeds.",
"default": "recent"
},
"startUrls": {
"title": "π Advanced: start URLs",
"type": "array",
"description": "LinkedIn job search URLs copied from the browser. Search filters from the URL are used as the query.",
"default": [],
"items": {
"type": "object",
"required": [
"url"
],
"properties": {
"url": {
"type": "string",
"title": "URL of a web page",
"format": "uri"
}
}
}
},
"proxyConfiguration": {
"title": "π‘ Proxy",
"type": "object",
"description": "Network egress configuration. Use the default unless you need a custom proxy setup.",
"default": {
"useApifyProxy": true
}
},
"linkedinHost": {
"title": "π LinkedIn host",
"type": "string",
"description": "Subdomain (e.g. \"www\", \"de\"). Affects default geo-routing + UI labels.",
"default": "www"
},
"outputLanguage": {
"title": "π£ Accept-Language",
"type": "string",
"description": "HTTP Accept-Language header. Default en-US for parsing-cleanliness.",
"default": "en-US,en;q=0.9"
},
"incrementalMode": {
"title": "π Incremental mode",
"type": "boolean",
"description": "Persist seen-jobIds across runs; emit only NEW + UPDATED. Requires stateKey.",
"default": false
},
"stateKey": {
"title": "π State key",
"type": "string",
"description": "Optional stable identifier for the tracked search universe. Leave empty to auto-derive a stable identifier from your search inputs β different keyword/location/filter combinations get isolated state automatically."
},
"allowNonIncrementalFallback": {
"title": "β©οΈ Allow Non-Incremental Fallback",
"type": "boolean",
"description": "If incremental mode is requested but the state store is not accessible on this account, fall back to a non-incremental run instead of failing. Default: fail loudly so missing state is not silently ignored.",
"default": false
},
"outputMode": {
"title": "π€ Output mode",
"enum": [
"all",
"new-only",
"changed-only"
],
"type": "string",
"description": "Which items to emit when in incrementalMode.",
"default": "all"
},
"emitUnchanged": {
"title": "β»οΈ Emit UNCHANGED items",
"type": "boolean",
"description": "Include items that haven't changed since last run.",
"default": false
},
"emitExpired": {
"title": "β°οΈ Emit EXPIRED items",
"type": "boolean",
"description": "Include items that disappeared from search results.",
"default": false
},
"skipReposts": {
"title": "Skip detected reposts",
"type": "boolean",
"description": "Suppress jobs with the same content as a previously-seen but inactive listing.",
"default": false
},
"enrichDetails": {
"title": "π¬ Enrich with detail page",
"type": "boolean",
"description": "Fetch each job's detail page for full description, seniorityLevel, employmentType, jobFunction, industry, and applicantCount. Adds 1 HTTP request per job.",
"default": false
},
"scrapeCompany": {
"title": "π’ Scrape company details",
"type": "boolean",
"description": "For each job, fetch the employer's public LinkedIn company page and add company description, website, employee count, logo, and address. Fetched once per unique company.",
"default": false
},
"discoverRelated": {
"title": "π Expand via relatedJobs",
"type": "boolean",
"description": "After the main SERP, fetch LinkedIn's relatedJobs feed for the first N results to discover jobs that don't surface on the keyword search. Useful for thin markets.",
"default": false
},
"relatedSeedCount": {
"title": "relatedJobs seed count",
"minimum": 0,
"maximum": 100,
"type": "integer",
"description": "How many of the first SERP results are used as seeds for relatedJobs expansion. Each seed yields up to 10 candidates.",
"default": 5
},
"telegramToken": {
"title": "Telegram bot token",
"type": "string",
"description": "Bot token from @BotFather. Leave empty to disable Telegram notifications."
},
"telegramChatId": {
"title": "π¬ Telegram chat ID",
"type": "string",
"description": "Numeric chat or channel ID where notifications should be sent."
},
"discordWebhookUrl": {
"title": "Discord webhook URL",
"type": "string",
"description": "Channel webhook URL. Leave empty to disable Discord notifications."
},
"slackWebhookUrl": {
"title": "Slack webhook URL",
"type": "string",
"description": "Incoming webhook URL. Leave empty to disable Slack notifications."
},
"whatsappAccessToken": {
"title": "WhatsApp Cloud API access token",
"type": "string",
"description": "Permanent System User token from Meta Business."
},
"whatsappPhoneNumberId": {
"title": "WhatsApp phone-number ID",
"type": "string",
"description": "Numeric phone-number ID from the Meta dashboard."
},
"whatsappTo": {
"title": "WhatsApp recipient (E.164)",
"type": "string",
"description": "Recipient phone number in E.164 format (e.g. \"4561234567\")."
},
"webhookUrl": {
"title": "Generic webhook URL (n8n / Make / Zapier)",
"type": "string",
"description": "Receives a JSON POST of {metadata, items} for each batch."
},
"webhookHeaders": {
"title": "Webhook headers",
"type": "object",
"description": "Additional HTTP headers to include with the generic webhook (e.g. Authorization)."
},
"notificationLimit": {
"title": "Max items per notification batch",
"minimum": 1,
"maximum": 50,
"type": "integer",
"description": "Cap on items included in each notification message.",
"default": 5
},
"notifyOnlyChanges": {
"title": "Notify only NEW/UPDATED",
"type": "boolean",
"description": "When in incrementalMode, suppress notifications for UNCHANGED items.",
"default": false
},
"compact": {
"title": "Compact output",
"type": "boolean",
"description": "Emit only core fields (keeps cost the same; reduces dataset size).",
"default": false
},
"descriptionMaxLength": {
"title": "Description max length",
"minimum": 0,
"type": "integer",
"description": "Truncate description (0 = no truncation). Only relevant when enrichDetails=true.",
"default": 0
},
"phoneExtractionMode": {
"title": "Phone-extraction mode",
"enum": [
"strict",
"lenient"
],
"type": "string",
"description": "\"strict\" requires Tel:/+CC prefix; \"lenient\" also picks up bare local-format numbers.",
"default": "strict"
},
"maxResults": {
"title": "π― Max results",
"minimum": 0,
"type": "integer",
"description": "Cap on emitted items (0 = unlimited).",
"default": 100
},
"descriptionFormat": {
"title": "Description format",
"enum": [
"all",
"text",
"html",
"markdown"
],
"type": "string",
"description": "Pick a single description representation. `all` keeps every variant; `text` / `html` / `markdown` drop the others.",
"default": "all"
},
"excludeEmptyFields": {
"title": "Exclude empty fields from output",
"type": "boolean",
"description": "Drop null, empty-string, and empty-array fields from each record before push. Smaller payloads for AI agents and dashboards.",
"default": false
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```