# LinkedIn Jobs Scraper β Pay only for new or changed listings (`blackfalcondata/linkedin-jobs-scraper`) Actor
Scrape linkedin.com jobs β title, company, location, salary, full description, apply URL, contact email β with state-keyed delta pricing. Recurring runs only charge for new or changed listings; already-seen jobs are skipped. Telegram/Discord/Slack/WhatsApp/webhook notifications.
- **URL**: https://apify.com/blackfalcondata/linkedin-jobs-scraper.md
- **Developed by:** [Black Falcon Data](https://apify.com/blackfalcondata) (community)
- **Categories:** Jobs, Lead generation, Automation
- **Stats:** 3 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet
## 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 Jobs Scraper do?
LinkedIn Jobs Scraper extracts structured job data from [linkedin.com](https://linkedin.com) β including salary data, contact details (email, apply URL), company metadata, full descriptions, and location data. It supports location filters and controllable result limits, so you can run the same query consistently over time.
### Key features
- π **Incremental mode (delta pricing)** β recurring runs only emit and charge for listings that are new or whose tracked content changed. Pair with Apify Schedules to run hourly or daily and pay 90%+ less than full re-scrapes.
- π **Detail enrichment** β fetch full job descriptions, criteria (seniority level, employment type, industry, job function, workplace type), applicant counts, and posting benefits. Toggle on with `enrichDetails: true`. Description is returned as plain text, HTML, and Markdown.
- π **Cross-region in one run** β combine `geoIds[]`, `regions[]` (ISO-2 codes), and 11 built-in presets (`nordic`, `dach`, `benelux`, `uk-ireland`, `eu-27`, `gcc`, `mena`, `asean`, `anglosphere`, `latam`, `nordics-extended`). Results are deduped on `jobId`.
- π― **Powerful filters** β `keywords`, `datePosted` (including unique `lastHour`), `jobType`, `experienceLevel`, `workType` (onsite/remote/hybrid), `salaryMin`/`salaryMax`, `companies`, `excludeCompanies`, `excludeKeywords`, `removeAgency`, `easyApply`, `distance`, and `sortBy`.
- π **Related-jobs discovery** β set `discoverRelated: true` to expand seed jobs with LinkedIn's own related-jobs feed. Adds 10-30% more relevant matches on thin-market queries, deduped against the main result set.
- β»οΈ **Repost detection** β when a previously expired listing reappears with matching content, it is flagged with `isRepost: true` and `repostOfId`. Set `skipReposts: true` to filter them out of the dataset.
- π¦ **Compact mode** β `compact: true` returns core fields only (AI-agent / MCP-friendly). Cuts payload by 80%+ when piping into LLMs.
- βοΈ **Description truncation** β cap `descriptionMaxLength` to control output size and per-record cost when feeding pipelines that don't need full text.
- π **Notifications built-in** β push results to Telegram, Discord, Slack, WhatsApp, or a custom webhook (n8n / Make / Zapier) after each run. Pair with `notifyOnlyChanges` to alert only on new or updated jobs.
- π **No login required** β uses LinkedIn's public guest-jobs endpoints. Datacenter proxies are sufficient; no account credentials required.
### 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`), contact and apply information (`applyUrl`, `applyType`, `easyApply`, and `extractedEmails`), 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 Free-text location (e.g. "Copenhagen, Denmark", "United States"). Use geoIds for higher precision.
- **`geoIds`** β Numeric LinkedIn geoIds (e.g. "103644278" = United States). 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 35 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
}
```
### 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 Jobs Scraper](https://apify.com/blackfalcondata/linkedin-jobs-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.
- Track salary trends across regions and categories over time.
- Monitor new and changed listings on scheduled runs without processing the full dataset every time.
- Build outreach lists using contact details and apply URLs from listings.
- 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 Jobs 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:** $0.001 per job record
Example costs:
- 10 results: **$0.01**
- 100 results: **$0.1**
- 500 results: **$0.5**
#### 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 | $0.25 | $0.01 | $0.24 (95%) | $0.39 |
| 15% β moderate broad query | $0.25 | $0.04 | $0.21 (85%) | $1.14 |
| 30% β high-volume aggregator | $0.25 | $0.08 | $0.17 (70%) | $2.27 |
Full re-scrape monthly cost at daily polling: $7.51. First month with incremental costs $0.63 / $1.35 / $2.44 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 Jobs 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 Jobs Scraper with other apps?
Yes. LinkedIn Jobs 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 Jobs 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 Jobs 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-jobs-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 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](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 - Jobs from the Middle East](https://apify.com/blackfalcondata/bayt-scraper?fpr=1h3gvi) β Scrape bayt.com - the leading Middle East job board. Salary data, experience requirements.
- [Bilbasen Scraper - Denmarkβs Car Marketplace](https://apify.com/blackfalcondata/bilbasen-scraper?fpr=1h3gvi) β Scrape bilbasen.dk - Denmarkβs largest car marketplace. Full vehicle specifications, seller.
### 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`):
Free-text location (e.g. "Copenhagen, Denmark", "United States"). Use geoIds for higher precision.
## `geoIds` (type: `array`):
Numeric LinkedIn geoIds (e.g. "103644278" = United States). 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`):
Direct LinkedIn job-search URLs. Supersedes structured query when set. Deferred to v0.5 β currently logged but not crawled.
## `proxyConfiguration` (type: `object`):
Network egress configuration. The default auto-selects whatever group your plan has available β switch to residential if you observe blocks.
## `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`):
Unique key for cross-run state. Required when incrementalMode=true.
## `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.
## `scopePerQuery` (type: `boolean`):
Reserved β currently no-op (state is per-stateKey).
## `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).
## 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,
"outputMode": "all",
"emitUnchanged": false,
"emitExpired": false,
"skipReposts": false,
"enrichDetails": false,
"scopePerQuery": false,
"discoverRelated": false,
"relatedSeedCount": 5,
"notificationLimit": 5,
"notifyOnlyChanges": false,
"compact": false,
"descriptionMaxLength": 0,
"phoneExtractionMode": "strict",
"maxResults": 100
}
```
# 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,
"scopePerQuery": false,
"discoverRelated": false,
"compact": false
};
// Run the Actor and wait for it to finish
const run = await client.actor("blackfalcondata/linkedin-jobs-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,
"scopePerQuery": False,
"discoverRelated": False,
"compact": False,
}
# Run the Actor and wait for it to finish
run = client.actor("blackfalcondata/linkedin-jobs-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,
"scopePerQuery": false,
"discoverRelated": false,
"compact": false
}' |
apify call blackfalcondata/linkedin-jobs-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=blackfalcondata/linkedin-jobs-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "LinkedIn Jobs Scraper β Pay only for new or changed listings",
"description": "Scrape linkedin.com jobs β title, company, location, salary, full description, apply URL, contact email β with state-keyed delta pricing. Recurring runs only charge for new or changed listings; already-seen jobs are skipped. Telegram/Discord/Slack/WhatsApp/webhook notifications.",
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"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": "Free-text location (e.g. \"Copenhagen, Denmark\", \"United States\"). Use geoIds for higher precision."
},
"geoIds": {
"title": "π LinkedIn geoIds",
"type": "array",
"description": "Numeric LinkedIn geoIds (e.g. \"103644278\" = United States). 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": "Direct LinkedIn job-search URLs. Supersedes structured query when set. Deferred to v0.5 β currently logged but not crawled.",
"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. The default auto-selects whatever group your plan has available β switch to residential if you observe blocks.",
"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": "Unique key for cross-run state. Required when incrementalMode=true."
},
"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
},
"scopePerQuery": {
"title": "Scope state per query",
"type": "boolean",
"description": "Reserved β currently no-op (state is per-stateKey).",
"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
}
}
},
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"type": "object",
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"defaultKeyValueStoreId": {
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"usage": {
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},
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},
"PROXY_SERPS": {
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}
},
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}
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}
}
}
}
}
}
```