# LinkedIn Jobs Scraper (`agentx/linkedin-jobs-scraper`) Actor LinkedIn Jobs API across 72 countries. Each posting returns the full LinkedIn taxonomy — title, seniority, function, required skills, salary (FX-normalized) — plus native company signals (headcount band, industry, founding year) and the hiring company's verified email and phone. - **URL**: https://apify.com/agentx/linkedin-jobs-scraper.md - **Developed by:** [AgentX](https://apify.com/agentx) (community) - **Categories:** Jobs, Lead generation, Agents - **Stats:** 186 total users, 29 monthly users, 100.0% runs succeeded, 6 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $2.50 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## LinkedIn Hiring Scraper - Job Market Intelligence & Talent Analytics API **LinkedIn Hiring Scraper is a global talent intelligence API that extracts structured LinkedIn job listings, salary ranges, skill requirements, and company firmographics across 70+ countries in a single keyword/location-driven run.** LinkedIn Hiring Scraper returns 30+ structured fields per job, including job title, job ID, LinkedIn job URL, company name, company LinkedIn URL, employee count, headquarters, salary range (min/max/currency), job level, employment type, remote work flag, required skill array, posting date, application count, full job description, location, and country code. Coverage spans LinkedIn jobs in 70+ countries. Built for talent market analysis, salary benchmarking, competitive hiring intelligence, workforce planning, ATS feeds, recruitment-firm prospecting, and labor-market dataset construction. Up to 10,000 job records per run at $0.0027 per result, with pay-per-result pricing and no monthly minimum. [![LinkedIn](https://img.shields.io/badge/LinkedIn-0077B5?style=for-the-badge&color=0077B5)](https://apify.com/agentx/linkedin-hiring-scraper?fpr=aiagentapi) [![Hiring Intelligence](https://img.shields.io/badge/Hiring_Intelligence-0077B5?style=for-the-badge&color=0077B5)](https://apify.com/agentx/linkedin-hiring-scraper?fpr=aiagentapi) [![Pay Per Result](https://img.shields.io/badge/Pay_Per_Result-0077B5?style=for-the-badge&color=0077B5)](https://apify.com/agentx/linkedin-hiring-scraper?fpr=aiagentapi) --- ### Why Choose This API #### The Most Complete LinkedIn Job Intelligence Dataset for Hiring Analytics **💰 Salary Range Intelligence** Extract `salary_minimum`, `salary_maximum`, `salary_currency`, and `salary_period` per job listing — enabling structured compensation benchmarking across 70+ countries without manual salary research. **🎯 Job Level & Function Classification** The `job_level` (Junior/Mid/Senior/Manager) and `job_function` fields enable workforce composition analysis and seniority distribution mapping across companies, industries, and markets. **🔑 Required Skills Extraction** The `skills` field captures the technology stack, certifications, and competencies required per role — enabling skills demand analysis, market fit scoring, and hiring trend research at scale. **📅 Posting Date & Hiring Velocity** The `posted_since` filter and `posted_date` field support time-windowed hiring velocity analysis — identify when companies rapidly scale specific teams as leading indicators of product launches, funding events, or market expansion. **🏢 Full Company Firmographics Per Listing** Every job record includes `company_type`, `company_founded`, `company_industry`, `employee_count`, `company_revenue`, and `company_rating` — delivering account-level intelligence embedded in every job data point for single-query CRM enrichment. **🏠 Remote Work Intelligence** Filter by `remote_only` and extract `is_remote` and `work_from_home` fields per listing — enabling distributed workforce research, remote talent pool mapping, and remote hiring trend analysis by market. **🌍 70+ Country Coverage** Target job listings across 70+ countries from Argentina to Vietnam — the broadest LinkedIn market coverage for global hiring intelligence and multi-market workforce analytics. --- ### Quick Start Guide #### How to Extract LinkedIn Job Data in 3 Steps ##### Step 1: Define Your Search Enter a job title, skill, or company name, select the target country, and configure optional filters for remote work, location, date range, and job type. ##### Step 2: Configure and Run the Actor [Open Actor Input](https://console.apify.com/actors/nmdyrR62YooFl1bBS/input?fpr=aiagentapi) Set your keyword, country, max results, and any filters, then click **Start**. ##### Step 3: Download Your Data Export results as JSON or CSV, or access programmatically via the Apify dataset API. Each record contains structured job data including salary, skills, company firmographics, and more. --- ### Input Parameters #### Configuration Fields | Parameter | Type | Required | Description | Example Values | | -------------- | ---------- | -------- | ------------------------------------------- | ------------------------------------------------- | | `keyword` | string | ✅ | Job title, skill, or company name to search | `"Product Manager"`, `"Data Engineer"`, `"React"` | | `country` | select | ✅ | Target market for job listing extraction | `"Germany"`, `"United States"`, `"Singapore"` | | `max_results` | integer | ✅ | Maximum job records to extract (10–10,000) | `100`, `500`, `1000` | | `remote_only` | checkbox | ❌ | Restrict results to remote positions | `true`, `false` | | `distance` | integer | ❌ | Search radius in miles (50–10,000) | `100`, `200` | | `location` | string | ❌ | City or region to focus results | `"Berlin"`, `"New York"` | | `posted_since` | datepicker | ❌ | Filter by posting recency | `"1 week"`, `"3 months"` | | `job_type` | select | ❌ | Employment type filter | `"full-time"`, `"contract"` | | `currency` | select | ❌ | Salary currency normalization | `"USD"`, `"EUR"`, `"GBP"` | **Supported Countries:** 70+ including United States, Germany, United Kingdom, France, Netherlands, Singapore, India, Australia, Canada, and more. #### Example Input Configuration ```json { "keyword": "Senior Data Engineer", "country": "United States", "max_results": 500, "posted_since": "1 month", "remote_only": false } ```` *** ### Output Data Schema #### Complete Job Record Structure Each extracted LinkedIn job record contains the following fields: [Open Actor Output](https://console.apify.com/actors/nmdyrR62YooFl1bBS/input?fpr=aiagentapi) #### Core Job Fields | Field | Type | Description | | --------------------- | ------- | ------------------------------------------ | | `processor` | string | Apify actor URL that processed this record | | `processed_at` | string | ISO 8601 timestamp (UTC) when scraped | | `platform` | string | Platform label (LinkedIn) | | `platform_url` | string | Job listing URL on LinkedIn | | `official_url` | string | Direct URL to original job posting | | `title` | string | Job title | | `posted_date` | string | Date job was posted | | `location` | string | Job location | | `is_remote` | boolean | Remote work indicator | | `description` | string | Full job description | | `job_type` | string | Employment type | | `job_level` | string | Seniority level | | `job_function` | string | Job category/department | | `skills` | string | Required skills and technologies | | `work_from_home` | string | Remote/hybrid arrangement details | | `vacancy_count` | integer | Number of open positions | | `experience_range` | string | Required years of experience | | `salary_period` | string | Pay frequency (yearly/monthly/hourly) | | `salary_minimum` | number | Minimum salary | | `salary_maximum` | number | Maximum salary | | `salary_currency` | string | Salary currency code | | `easy_apply` | boolean | LinkedIn Easy Apply indicator | | `company_name` | string | Hiring company name | | `company_type` | string | Company ownership type | | `company_founded` | integer | Year founded | | `company_industry` | string | Industry/sector | | `company_url` | string | LinkedIn company profile URL | | `company_website` | string | Official company website | | `company_logo` | string | Company logo URL | | `company_addresses` | string | Physical office address | | `company_revenue` | string | Estimated annual revenue range | | `company_description` | string | Company about section | | `company_rating` | number | Overall company rating | | `employee_count` | string | Approximate employee count | | `review_count` | integer | Number of employee reviews | | `emails` | array | Contact emails | | `phones` | array | Contact phone numbers | | `social_links` | object | Company social media URLs | #### Example JSON Output ```json { "processor": "https://apify.com/agentx/linkedin-hiring-scraper?fpr=aiagentapi", "processed_at": "2026-05-01T10:30:00.000Z", "platform": "LinkedIn", "title": "Senior Software Engineer", "posted_date": "2026-04-28", "location": "San Francisco, CA", "is_remote": false, "job_type": "Full-time", "job_level": "Senior", "job_function": "Engineering", "skills": "Python, JavaScript, React, Node.js, AWS", "salary_minimum": 140000, "salary_maximum": 180000, "salary_currency": "USD", "salary_period": "yearly", "company_name": "Acme Corporation", "company_industry": "Software Development", "employee_count": "1000-5000" } ``` #### Export Formats - **JSON** - Complete structured data with all metadata - **CSV** - Spreadsheet-compatible for ATS, BI, and analytics tools - **API Access** - Programmatic access via Apify Client SDK - **Cloud Storage** - Automatic upload to Apify Dataset *** ### Integration Examples #### Actor ID for Platform Integration ```text nmdyrR62YooFl1bBS ``` #### Ⓜ️ [Make.com Setup:](https://www.make.com/en/register?pc=marketingme) 1. Login to **[Make.com (Get 1000 Free Credits)](https://www.make.com/en/register?pc=marketingme)** 2. Add module **"Run an Actor"** 3. Turn **'Map'** on - right side of the 'Actor\*' 4. Paste **Actor ID** - from above 5. Click the **'⟳ Refresh'** - left side of Map 6. **Input JSON\*** - Modify the parameters as needed 7. Set **"Run synchronously"** to **YES** 8. Add module **"Get Dataset Items"** - receive the result 9. In **Dataset ID\*** select **defaultDatasetId** #### 🎱 [N8N.io Setup:](https://n8n.io/) 1. Add **'Run an Actor and get dataset'** - from the apify node 2. **Actor** → **By ID** → **Paste Actor ID** - from above 3. **Input JSON** - Modify the parameters as needed #### Python Integration Example ```python from apify_client import ApifyClient client = ApifyClient('YOUR_API_TOKEN') run_input = { "keyword": "Machine Learning Engineer", "country": "United States", "max_results": 500, "posted_since": "1 month" } run = client.actor("nmdyrR62YooFl1bBS").call(run_input=run_input) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ``` #### JavaScript/Node.js Integration ```javascript import { ApifyClient } from "apify-client"; const client = new ApifyClient({ token: "YOUR_API_TOKEN" }); const input = { keyword: "Product Manager", country: "Germany", max_results: 200, remote_only: false, }; const run = await client.actor("nmdyrR62YooFl1bBS").call(input); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => console.log(item)); ``` #### JSON-LD Metadata ```json { "@context": "https://schema.org", "@graph": [ { "@type": "SoftwareApplication", "@id": "https://apify.com/agentx/linkedin-hiring-scraper#software", "name": "LinkedIn Hiring Scraper", "description": "LinkedIn Hiring Scraper is a job market intelligence API delivering structured job listings with salary ranges, skills, job levels, company firmographics, and remote work signals across 70+ countries for talent analytics.", "applicationCategory": "BusinessApplication", "applicationSubCategory": "Web Scraping API", "operatingSystem": "Web, Cloud", "url": "https://apify.com/agentx/linkedin-hiring-scraper?fpr=aiagentapi", "softwareVersion": "1.0.0", "datePublished": "2024-08-01", "dateModified": "2026-05-01", "featureList": [ "30+ structured fields per LinkedIn job posting", "Salary range (min/max/currency) per job", "Required skill array and job level signals", "Company firmographics: name, employee count, HQ", "Remote work flag and employment type", "70+ country coverage", "Up to 10,000 job records per run at $0.0027/result", "Native integrations with Make.com, n8n, LangChain, and CrewAI" ], "offers": { "@type": "Offer", "price": "0.0027", "priceCurrency": "USD", "availability": "https://schema.org/InStock" }, "author": { "@id": "https://apify.com/agentx#person" }, "publisher": { "@id": "https://apify.com#organization" } }, { "@type": "Person", "@id": "https://apify.com/agentx#person", "name": "AgentX", "url": "https://apify.com/agentx", "sameAs": [ "https://apify.com/agentx", "https://t.me/AiAgentApi", "https://t.me/Apify_Actor" ], "knowsAbout": [ "web scraping", "LinkedIn", "hiring intelligence", "talent analytics", "salary benchmarking" ] }, { "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": 1, "name": "Apify", "item": "https://apify.com" }, { "@type": "ListItem", "position": 2, "name": "AgentX", "item": "https://apify.com/agentx" }, { "@type": "ListItem", "position": 3, "name": "LinkedIn Hiring Scraper", "item": "https://apify.com/agentx/linkedin-hiring-scraper" } ] } ] } ``` *** ### Pricing & Cost Calculator #### Pay-Per-Result Pricing | Event | Price | | ------------------- | --------------- | | Actor Start | $0.01 per run | | Job Result (BRONZE) | $0.0027 per job | #### Cost Examples | Volume | Estimated Cost | | ----------- | -------------- | | 100 jobs | ~$0.28 | | 500 jobs | ~$1.36 | | 1,000 jobs | ~$2.71 | | 5,000 jobs | ~$13.51 | | 10,000 jobs | ~$27.01 | > Start with a free Apify account — new accounts include free compute credits to test the actor at no cost. *** ### Use Cases & Applications #### Talent Market Intelligence **Competitor Hiring Velocity Analysis** Search competitor company names as keywords with `posted_since` filters to detect rapid team expansion — surfacing hiring acceleration signals that indicate product launches, funding events, or market entry initiatives. **Global Salary Benchmarking** Extract salary data across 70+ countries for target roles to build geographic compensation benchmarks — normalizing `salary_minimum`, `salary_maximum`, and `salary_currency` across markets for total compensation planning. **Skills Demand Mapping** Aggregate `skills` fields across thousands of job listings in a target function to identify the most in-demand technologies and certifications — feeding workforce planning, training investment, and product roadmap decisions. #### Recruitment Analytics **Job Level Distribution Analysis** Use `job_level` and `job_function` to analyze seniority distribution across companies or industries — identifying whether teams are scaling junior IC roles, building management layers, or seeking specialist expertise. **ATS Pipeline Enrichment** Push structured LinkedIn job data into ATS or candidate matching platforms — enriching each job record with salary ranges, skill requirements, and full company firmographics for precision candidate-to-role matching. #### Market Research **Industry Hiring Trend Analysis** Filter by `company_industry` and `posted_date` to track which sectors are accelerating or decelerating hiring across global markets — building leading indicator datasets for economic research and market intelligence products. **Remote Work Policy Benchmarking** Filter with `remote_only` and analyze `work_from_home` field distributions to measure remote work adoption rates by company size, industry, and geography across LinkedIn's 70+ markets. *** ### FAQ #### How many countries does this actor cover? 70+ countries including all major markets in North America, Europe, Asia-Pacific, Middle East, Latin America, and Africa. #### Does this actor extract salary data for all jobs? Salary data is extracted when posted on the LinkedIn listing. Not all employers disclose salary on LinkedIn. When available, `salary_minimum`, `salary_maximum`, `salary_currency`, and `salary_period` are all extracted. #### Can I search by company name to track competitor hiring? Yes. Enter a company name as the `keyword` to extract all open jobs for that company in the target country. #### What does `easy_apply` mean? `true` indicates the job can be applied to directly on LinkedIn without leaving the platform — a useful signal for filtering high-access job listings. #### Can I combine this with LinkedIn Company Scraper? Yes. Use [LinkedIn Company Scraper](https://apify.com/agentx/linkedin-company-scraper?fpr=aiagentapi) to get company URLs from job listings and enrich with full firmographic profiles including office locations, featured employees, and recent updates. *** ### SEO Keywords & Search Terms #### Primary Keywords LinkedIn job scraper API, LinkedIn hiring intelligence API, LinkedIn salary data extraction, LinkedIn jobs data pipeline, talent market analytics API, LinkedIn competitor hiring analysis, LinkedIn skills demand API, workforce analytics LinkedIn, job market intelligence API, LinkedIn recruitment data #### Long-Tail Keywords how to extract LinkedIn job listings programmatically, LinkedIn salary benchmark API, competitor hiring velocity analysis LinkedIn, skills demand mapping LinkedIn, remote work analysis LinkedIn API, LinkedIn job level distribution data, ATS enrichment LinkedIn job data, multi-country LinkedIn job intelligence, hiring trend analysis LinkedIn, talent intelligence pipeline LinkedIn #### Industry Terms LinkedIn job intelligence, talent market analytics, salary range extraction API, hiring velocity signals, skills demand data, workforce composition analysis, remote work intelligence, competitive hiring data, job market research API, ATS data enrichment #### Use Case Keywords LinkedIn data pipeline, talent analytics platform, hiring intelligence tool, salary benchmarking API, competitive hiring tracker, skills gap analysis LinkedIn, remote hiring trend analysis, job market research tool, workforce planning intelligence, ATS enrichment pipeline *** ### Trust & Certifications - ✅ **Production-Grade Infrastructure** — runs on the Apify cloud platform with managed proxy rotation and automatic retries - ✅ **GDPR & CCPA Aligned** — extracts only publicly available LinkedIn job postings; no personal candidate data inferred or retained beyond the run session - ✅ **Pay-Per-Result Billing** — transparent per-job pricing with no monthly minimum or seat fees - ✅ **Continuously Maintained** — schema and selector updates released as LinkedIn evolves *** ### Legal & Compliance #### Data Rights & Usage All data extracted by this actor originates from publicly available LinkedIn job listings. Users are responsible for ensuring their use of extracted data complies with applicable laws and LinkedIn's terms of service. #### Privacy Compliance - **GDPR**: Compliant with EU General Data Protection Regulation. Only publicly available job listing data is extracted. - **CCPA**: Compliant with California Consumer Privacy Act requirements. #### Platform Terms of Service Users must review and comply with LinkedIn's terms of service when using extracted data. #### Enterprise Support For enterprise licensing, custom integrations, or compliance inquiries: - **Telegram**: [@AiAgentApi](https://t.me/AiAgentApi) *** ### Related Tools #### Jobs & Hiring - **[All Jobs Scraper](https://apify.com/agentx/all-jobs-scraper?fpr=aiagentapi)** - Multi-Platform Job Listings Intelligence API - **[Glassdoor Hiring Scraper](https://apify.com/agentx/glassdoor-hiring-scraper?fpr=aiagentapi)** - Glassdoor Job Listings Intelligence API - **[Glints Employer Data Extractor](https://apify.com/agentx/glints-employer-data-extractor?fpr=aiagentapi)** - Glints Employer Intelligence API - **[Glints Jobs Data Extractor](https://apify.com/agentx/glints-jobs-data-extractor?fpr=aiagentapi)** - Glints Job Listings Intelligence API - 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Zomato Restaurant Search Intelligence API #### Other - **[Global Weather Scraper](https://apify.com/agentx/global-weather-scraper?fpr=aiagentapi)** - Global Weather Intelligence API *** ### Support & Community - **👥 Community**: [@Apify\_Actor](https://t.me/Apify_Actor) - **👤 Contact Team**: [@AiAgentApi](https://t.me/AiAgentApi) *** **Last Updated:** May 01, 2026 # Actor input Schema ## `keyword` (type: `string`): Job title, skill, or company name to search for ## `country` (type: `string`): Country where the target job listings are located ## `max_results` (type: `integer`): Maximum number of jobs to return ## `remote_only` (type: `boolean`): Restrict results to remote-friendly positions only ## `distance` (type: `integer`): Search radius in miles around the specified location ## `location` (type: `string`): City or region to focus the job search results on ## `posted_since` (type: `string`): Only include listings posted within this timeframe ## `job_type` (type: `string`): Employment type to filter by: full-time, contract, etc. ## `currency` (type: `string`): Target currency for converting salary figures ## Actor input object example ```json { "keyword": "Manager", "country": "United States", "max_results": 10, "distance": 200, "posted_since": "3 months", "job_type": "all", "currency": "USD" } ``` # Actor output Schema ## `results` (type: `string`): All job listings found across platforms with full details including salary, company info, and contact details # 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 = { "keyword": "Manager", "country": "United States", "max_results": 10, "remote_only": false, "distance": 200, "posted_since": "3 months", "job_type": "all", "currency": "USD" }; // Run the Actor and wait for it to finish const run = await client.actor("agentx/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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "keyword": "Manager", "country": "United States", "max_results": 10, "remote_only": False, "distance": 200, "posted_since": "3 months", "job_type": "all", "currency": "USD", } # Run the Actor and wait for it to finish run = client.actor("agentx/linkedin-jobs-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keyword": "Manager", "country": "United States", "max_results": 10, "remote_only": false, "distance": 200, "posted_since": "3 months", "job_type": "all", "currency": "USD" }' | apify call agentx/linkedin-jobs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=agentx/linkedin-jobs-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Jobs Scraper", "description": "LinkedIn Jobs API across 72 countries. Each posting returns the full LinkedIn taxonomy — title, seniority, function, required skills, salary (FX-normalized) — plus native company signals (headcount band, industry, founding year) and the hiring company's verified email and phone.", "version": "1.0", "x-build-id": "NM8Yf4BizTabhd7AW" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/agentx~linkedin-jobs-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-agentx-linkedin-jobs-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/agentx~linkedin-jobs-scraper/runs": { "post": { "operationId": "runs-sync-agentx-linkedin-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/agentx~linkedin-jobs-scraper/run-sync": { "post": { "operationId": "run-sync-agentx-linkedin-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "keyword", "country", "max_results" ], "properties": { "keyword": { "title": "🔍 Keyword", "type": "string", "description": "Job title, skill, or company name to search for" }, "country": { "title": "🌍 Country", "enum": [ "Argentina", "Australia", "Austria", "Bahrain", "Bangladesh", "Belgium", "Bulgaria", "Brazil", "Canada", "Chile", "China", "Colombia", "Costa Rica", "Croatia", "Cyprus", "Czech Republic", "Denmark", "Ecuador", "Egypt", "Estonia", "Finland", "France", "Germany", "Greece", "Hong Kong", "Hungary", "India", "Indonesia", "Ireland", "Israel", "Italy", "Japan", "Kuwait", "Latvia", "Lithuania", "Luxembourg", "Malaysia", "Malta", "Mexico", "Morocco", "Netherlands", "New Zealand", "Nigeria", "Norway", "Oman", "Pakistan", "Panama", "Peru", "Philippines", "Poland", "Portugal", "Qatar", "Romania", "Saudi Arabia", "Singapore", "Slovakia", "Slovenia", "South Africa", "South Korea", "Spain", "Sweden", "Switzerland", "Taiwan", "Thailand", "Turkey", "Ukraine", "United Arab Emirates", "United Kingdom", "United States", "Uruguay", "Venezuela", "Vietnam" ], "type": "string", "description": "Country where the target job listings are located" }, "max_results": { "title": "📊 Max Results", "minimum": 10, "maximum": 10000, "type": "integer", "description": "Maximum number of jobs to return" }, "remote_only": { "title": "🏠 Remote Only", "type": "boolean", "description": "Restrict results to remote-friendly positions only" }, "distance": { "title": "🗺 Distance", "minimum": 50, "maximum": 10000, "type": "integer", "description": "Search radius in miles around the specified location" }, "location": { "title": "📍 Location", "type": "string", "description": "City or region to focus the job search results on" }, "posted_since": { "title": "📅 Posted Since", "type": "string", "description": "Only include listings posted within this timeframe" }, "job_type": { "title": "💼 Job Type", "enum": [ "all", "fulltime", "parttime", "internship", "contract" ], "type": "string", "description": "Employment type to filter by: full-time, contract, etc." }, "currency": { "title": "💱 Currency", "enum": [ "AED", "AFN", "ALL", "AMD", "ANG", "AOA", "ARS", "AUD", "AWG", "AZN", "BAM", "BBD", "BDT", "BGN", "BHD", "BIF", "BMD", "BND", "BOB", "BRL", "BSD", "BTN", "BWP", "BYN", "BZD", "CAD", "CDF", "CHF", "CLF", "CLP", "CNH", "CNY", "COP", "CRC", "CUP", "CVE", "CZK", "DJF", "DKK", "DOP", "DZD", "EGP", "ERN", "ETB", "EUR", "FJD", "FKP", "FOK", "GBP", "GEL", "GGP", "GHS", "GIP", "GMD", "GNF", "GTQ", "GYD", "HKD", "HNL", "HRK", "HTG", "HUF", "IDR", "ILS", "IMP", "INR", "IQD", "IRR", "ISK", "JEP", "JMD", "JOD", "JPY", "KES", "KGS", "KHR", "KID", "KMF", "KRW", "KWD", "KYD", "KZT", "LAK", "LBP", "LKR", "LRD", "LSL", "LYD", "MAD", "MDL", "MGA", "MKD", "MMK", "MNT", "MOP", "MRU", "MUR", "MVR", "MWK", "MXN", "MYR", "MZN", "NAD", "NGN", "NIO", "NOK", "NPR", "NZD", "OMR", "PAB", "PEN", "PGK", "PHP", "PKR", "PLN", "PYG", "QAR", "RON", "RSD", "RUB", "RWF", "SAR", "SBD", "SCR", "SDG", "SEK", "SGD", "SHP", "SLE", "SLL", "SOS", "SRD", "SSP", "STN", "SYP", "SZL", "THB", "TJS", "TMT", "TND", "TOP", "TRY", "TTD", "TVD", "TWD", "TZS", "UAH", "UGX", "USD", "UYU", "UZS", "VES", "VND", "VUV", "WST", "XAF", "XCD", "XCG", "XDR", "XOF", "XPF", "YER", "ZAR", "ZMW", "ZWG", "ZWL" ], "type": "string", "description": "Target currency for converting salary figures" } } }, "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 } } } } } } } } } } ```