# 🔥 LinkedIn Jobs Scraper (`powerai/linkedin-jobs-scraper-2`) Actor Scrape LinkedIn job search results. Get title, company, location, description, salary, and optional company details in clean JSON. - **URL**: https://apify.com/powerai/linkedin-jobs-scraper-2.md - **Developed by:** [PowerAI](https://apify.com/powerai) (community) - **Categories:** Jobs, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 Jobs Scraper Scrape jobs from LinkedIn public job search results. Paste one or more search URLs and extract title, company, location, description, salary snippets, employment type, and optional company details. ### ✨ Key Features - 🔗 Scrape from **LinkedIn job search URLs** (public / incognito version) - 💼 Job title, company, location, posted date, and applicants - 📝 Full **job description** (text + HTML) - 💰 Salary snippets when LinkedIn shows them - 🏢 Optional **company details** (website, employee count, about) - 🌍 Optional **city-split** to go beyond LinkedIn's ~1000 results per search - 📋 Structured JSON output, streamed while the run is in progress ### 💪 Why Choose This Actor? - **Focused**: Built for LinkedIn public job search extraction - **Flexible**: Multiple search URLs and optional company enrichment - **Efficient**: Results are pushed continuously while the job runs - **Structured**: Renamed, integration-friendly field names - **Reliable**: Stable public search-result extraction ### 🎯 Perfect For - 📊 Talent market and hiring trend research - 📬 Recruiting / agency lead generation - 🔔 Daily new-job monitoring with date filters - 🤖 Job board and CRM enrichment pipelines ### 📝 Input Requirements - `searchUrls` (required): One or more LinkedIn job search URLs - `maxJobs` (optional): Max jobs to scrape (minimum 10) - `includeCompanyDetails` (optional): Also scrape company firmographics. Default: `false` - `splitByCity` (optional): Split search by cities in a country. Default: `false` - `splitCountryCode` (optional): ISO country code when `splitByCity` is enabled, e.g. `US` #### Input Example ```json { "searchUrls": [ "https://www.linkedin.com/jobs/search/?keywords=software%20engineer&location=United%20States&f_WT=2" ], "maxJobs": 100, "includeCompanyDetails": false } ```` #### Output Example ```json { "jobId": "3692563200", "jobUrl": "https://www.linkedin.com/jobs/view/english-data-labeling-analyst-at-facebook-3692563200", "title": "English Data Labeling Analyst", "companyName": "Facebook", "location": "Los Angeles Metropolitan Area", "salaryRange": ["$17.00", "$19.00"], "postedAt": "2023-08-16", "employmentType": "Contract", "seniority": "Associate", "description": "APPROVED REMOTE LOCATIONS:...", "scrapedAt": "2026-07-21T07:00:00.000Z" } ``` ### 🚀 How to Use 1. Open LinkedIn Jobs in an **incognito** window and apply your filters 2. Copy the full search URL from the address bar into `searchUrls` 3. Optionally set `maxJobs` and `includeCompanyDetails` 4. Click **Start** and download results as JSON, CSV, Excel, or HTML ### 📌 Notes - This actor uses the **public** LinkedIn jobs search (no login). Advanced login-only filters may not apply - For more than ~1000 results per search, enable `splitByCity` with a `splitCountryCode` - To monitor new jobs daily, set LinkedIn's date filter to "Past 24 hours" in the search URL and schedule the run - Free users of this actor have run and result-size limits; upgrade for unlimited usage # Actor input Schema ## `searchUrls` (type: `array`): Open LinkedIn Jobs search in an incognito window (public version), apply filters, then paste the full URL(s) here. Multiple search URLs are supported. ## `maxJobs` (type: `integer`): Maximum number of jobs to scrape. ## `includeCompanyDetails` (type: `boolean`): Also scrape company about text, website, and employee count. Slower because each job needs an extra request. ## `splitByCity` (type: `boolean`): Split the search across cities in a country to bypass LinkedIn's ~1000 results-per-search limit. Overwrites the location filter in the search URLs. ## `splitCountryCode` (type: `string`): ISO country code used when Split search by cities is enabled, e.g. US, GB, DE. Required when splitByCity is true. ## Actor input object example ```json { "searchUrls": [ "https://www.linkedin.com/jobs/search/?keywords=software%20engineer&location=United%20States&f_WT=2" ], "maxJobs": 20, "includeCompanyDetails": false, "splitByCity": false, "splitCountryCode": "US" } ``` # 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 = { "searchUrls": [ "https://www.linkedin.com/jobs/search/?keywords=software%20engineer&location=United%20States&f_WT=2" ], "maxJobs": 20, "includeCompanyDetails": false, "splitByCity": false, "splitCountryCode": "US" }; // Run the Actor and wait for it to finish const run = await client.actor("powerai/linkedin-jobs-scraper-2").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 = { "searchUrls": ["https://www.linkedin.com/jobs/search/?keywords=software%20engineer&location=United%20States&f_WT=2"], "maxJobs": 20, "includeCompanyDetails": False, "splitByCity": False, "splitCountryCode": "US", } # Run the Actor and wait for it to finish run = client.actor("powerai/linkedin-jobs-scraper-2").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 '{ "searchUrls": [ "https://www.linkedin.com/jobs/search/?keywords=software%20engineer&location=United%20States&f_WT=2" ], "maxJobs": 20, "includeCompanyDetails": false, "splitByCity": false, "splitCountryCode": "US" }' | apify call powerai/linkedin-jobs-scraper-2 --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=powerai/linkedin-jobs-scraper-2", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "🔥 LinkedIn Jobs Scraper", "description": "Scrape LinkedIn job search results. Get title, company, location, description, salary, and optional company details in clean JSON.", "version": "0.0", "x-build-id": "mGfEo6hfdg3rHedOA" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/powerai~linkedin-jobs-scraper-2/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-powerai-linkedin-jobs-scraper-2", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/powerai~linkedin-jobs-scraper-2/runs": { "post": { "operationId": "runs-sync-powerai-linkedin-jobs-scraper-2", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/powerai~linkedin-jobs-scraper-2/run-sync": { "post": { "operationId": "run-sync-powerai-linkedin-jobs-scraper-2", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "searchUrls" ], "properties": { "searchUrls": { "title": "LinkedIn jobs search URLs", "type": "array", "description": "Open LinkedIn Jobs search in an incognito window (public version), apply filters, then paste the full URL(s) here. Multiple search URLs are supported.", "items": { "type": "string" }, "default": [ "https://www.linkedin.com/jobs/search/?keywords=software%20engineer&location=United%20States&f_WT=2" ] }, "maxJobs": { "title": "Max jobs", "minimum": 10, "type": "integer", "description": "Maximum number of jobs to scrape.", "default": 20 }, "includeCompanyDetails": { "title": "Include company details", "type": "boolean", "description": "Also scrape company about text, website, and employee count. Slower because each job needs an extra request.", "default": false }, "splitByCity": { "title": "Split search by cities", "type": "boolean", "description": "Split the search across cities in a country to bypass LinkedIn's ~1000 results-per-search limit. Overwrites the location filter in the search URLs.", "default": false }, "splitCountryCode": { "title": "Country code for city split", "type": "string", "description": "ISO country code used when Split search by cities is enabled, e.g. US, GB, DE. Required when splitByCity is true." } } }, "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 } } } } } } } } } } ```