# LinkedIn Jobs Scraper (`mighty_monk/linkedin-jobs-scraper`) Actor Scrape public LinkedIn job search results and job detail pages. Extract title, company, location, employment type, seniority, description, apply URL, posted date, and applicants info when public. - **URL**: https://apify.com/mighty\_monk/linkedin-jobs-scraper.md - **Developed by:** [Harsh](https://apify.com/mighty_monk) (community) - **Categories:** Jobs, Lead generation - **Stats:** 4 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 job scrapeds 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 public LinkedIn job search results and job detail pages** — title, company, location, workplace type, employment type, seniority, description, apply URL, posted date, and applicants (when public). Built with **TypeScript**, **Crawlee CheerioCrawler**, and LinkedIn **guest/public** job endpoints (no login required for many public listings). Run it on the [Apify platform](https://apify.com) for scheduling, API access, proxy rotation, monitoring, and dataset exports (JSON, CSV, Excel). ### What does LinkedIn Jobs Scraper do? Given LinkedIn job **search URLs** and/or **keywords + location**, this Actor: 1. Converts public search URLs into LinkedIn guest `seeMoreJobPostings` API requests 2. Paginates search results until `maxJobs` is reached 3. Optionally opens each job’s guest detail page for full description and criteria 4. Deduplicates jobs by `jobId` 5. Pushes structured dataset items 6. Exports **JOBS.csv** and **SUMMARY.md** to the key-value store ### Why use LinkedIn Jobs Scraper? - **Recruiting pipelines** — build candidate-role inventories from public listings - **Sales / lead generation** — find companies hiring for target roles - **Market research** — track job titles, locations, and seniority mix over time - **Competitive intel** — monitor which skills and roles competitors post ### How to scrape LinkedIn jobs 1. Open the Actor in [Apify Console](https://console.apify.com) 2. Paste a LinkedIn jobs search URL **or** set `keywords` + `location` 3. Set **Max jobs** and enable/disable full descriptions 4. Keep concurrency low and enable **Apify Proxy** (residential recommended) 5. Click **Start** 6. Download results from the **Dataset** tab or key-value store exports ### Input | Field | Type | Default | Description | | -------------------- | -------------- | -------------- | ------------------------------------------------ | | `searchUrls` | string[] | `[]` | Public LinkedIn job search URLs | | `keywords` | string | `""` | Keywords used to build a search URL | | `location` | string | `""` | Location paired with keywords | | `maxJobs` | integer | `50` | Max unique jobs (by jobId) | | `maxConcurrency` | integer | `2` | Concurrent HTTP requests | | `maxRequestRetries` | integer | `3` | HTTP retry count | | `requestDelayMs` | integer | `1000` | Delay used for rate limiting | | `proxyConfiguration` | object | Apify Proxy on | Proxy settings | | `includeDescription` | boolean | `true` | Fetch job detail pages for full description | Example (search URL): ```json { "searchUrls": [ "https://www.linkedin.com/jobs/search/?keywords=software%20engineer&location=United%20States" ], "maxJobs": 50, "maxConcurrency": 2, "maxRequestRetries": 3, "requestDelayMs": 1000, "proxyConfiguration": { "useApifyProxy": true }, "includeDescription": true } ```` Example (keywords + location): ```json { "keywords": "account executive", "location": "New York, United States", "maxJobs": 25, "includeDescription": true, "proxyConfiguration": { "useApifyProxy": true } } ``` See [`examples/input.json`](examples/input.json). ### Output Each dataset item is one job: ```json { "jobId": "4123456789", "title": "Senior Software Engineer", "company": "Acme Corp", "companyUrl": "https://www.linkedin.com/company/acme-corp", "location": "San Francisco, CA", "workplaceType": "Remote", "employmentType": "Full-time", "seniority": "Mid-Senior level", "description": "Build scalable backend services in TypeScript and Node.js...", "postedAt": "2026-07-01", "applicants": "Over 200 applicants", "applyUrl": "https://www.linkedin.com/jobs/view/4123456789/?isApplication=true", "jobUrl": "https://www.linkedin.com/jobs/view/4123456789", "scrapedAt": "2026-07-13T12:00:00.000Z", "error": null } ``` You can download the dataset as **JSON, HTML, CSV, or Excel**. The Actor also writes: | Key-value record | Description | | ---------------- | ---------------------------------- | | `JOBS.csv` | All job rows as CSV | | `SUMMARY.md` | Markdown summary table of results | ### Data fields | Field | Description | | ---------------- | ------------------------------------------------ | | `jobId` | LinkedIn job posting ID | | `title` | Job title | | `company` | Hiring company name | | `companyUrl` | LinkedIn company URL when available | | `location` | Location string from the listing | | `workplaceType` | Remote / Hybrid / On-site (inferred when possible) | | `employmentType` | Full-time, Part-time, Contract, etc. | | `seniority` | Seniority level when public | | `description` | Full text when `includeDescription` is true | | `postedAt` | Posted date or relative time | | `applicants` | Public applicants caption | | `applyUrl` | Application link when available | | `jobUrl` | Canonical public job URL | | `scrapedAt` | ISO scrape timestamp | | `error` | Soft error for blocked/partial records | ### Pricing **Pay-per-event (PPE):** **$0.003 per job** (dataset item), plus a small Actor-start fee. Estimate: 50 jobs ≈ **$0.15**. ### Tips - Prefer **Apify Proxy residential** if you hit auth walls, captchas, or empty results - Keep `maxConcurrency` at **1–3** and `requestDelayMs` around **1000–2000 ms** - Set `includeDescription: false` for faster/cheaper runs when you only need titles and companies - Use stable public search URLs from an incognito browser session - Unit tests use HTML fixtures so CI does not depend on live LinkedIn access ### Limitations - Scrapes **public/guest** LinkedIn job pages only — not authenticated feed data - LinkedIn frequently shows **auth walls** or rate limits; proxy + low concurrency help but do not guarantee 100% coverage - Cheerio parses **static HTML**. Heavily client-rendered views may return fewer fields - Some fields (applicants, apply URL, full description) are only present on detail pages - Respect LinkedIn Terms of Service and applicable laws; use data responsibly ### Technical notes - Search pagination uses\ `https://www.linkedin.com/jobs-guest/jobs/api/seeMoreJobPostings/search?...&start=N` - Job details use\ `https://www.linkedin.com/jobs-guest/jobs/api/jobPosting/{jobId}` - Extraction strategies: DOM job cards, JSON-LD `JobPosting`, job criteria lists - Graceful handling of auth walls / blocks: logs a warning and falls back to search-card data when detail is blocked ### Development ```bash cd factory/linkedin-jobs-scraper npm install npm test npm run build apify run ``` ### License Apache-2.0 # Actor input Schema ## `searchUrls` (type: `array`): One or more public LinkedIn job search URLs (e.g. https://www.linkedin.com/jobs/search/?keywords=software%20engineer\&location=United%20States). The Actor converts these to guest API endpoints for scraping. ## `keywords` (type: `string`): Job search keywords used when building a search URL (if searchUrls is empty or in addition to searchUrls). Example: software engineer. ## `location` (type: `string`): Location string paired with keywords (e.g. United States, Remote, San Francisco, CA). ## `maxJobs` (type: `integer`): Maximum number of unique jobs to scrape (deduplicated by jobId). ## `maxConcurrency` (type: `integer`): Maximum number of concurrent HTTP requests. Keep low (1–3) to reduce LinkedIn rate limits and auth walls. ## `maxRequestRetries` (type: `integer`): How many times to retry a failed HTTP request before giving up. ## `requestDelayMs` (type: `integer`): Approximate delay between requests used to compute rate limiting (max requests per minute). ## `proxyConfiguration` (type: `object`): Apify Proxy settings. Strongly recommended for LinkedIn (residential often works better). ## `includeDescription` (type: `boolean`): When true, visit each job detail page (guest jobPosting API) to extract full description, seniority, employment type, applicants, and apply URL. ## Actor input object example ```json { "searchUrls": [ "https://www.linkedin.com/jobs/search/?keywords=software%20engineer&location=United%20States" ], "keywords": "", "location": "", "maxJobs": 50, "maxConcurrency": 2, "maxRequestRetries": 3, "requestDelayMs": 1000, "proxyConfiguration": { "useApifyProxy": true }, "includeDescription": true } ``` # Actor output Schema ## `dataset` (type: `string`): No description ## `jobsCsv` (type: `string`): No description ## `summary` (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 = { "searchUrls": [ "https://www.linkedin.com/jobs/search/?keywords=software%20engineer&location=United%20States" ] }; // Run the Actor and wait for it to finish const run = await client.actor("mighty_monk/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 = { "searchUrls": ["https://www.linkedin.com/jobs/search/?keywords=software%20engineer&location=United%20States"] } # Run the Actor and wait for it to finish run = client.actor("mighty_monk/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 '{ "searchUrls": [ "https://www.linkedin.com/jobs/search/?keywords=software%20engineer&location=United%20States" ] }' | apify call mighty_monk/linkedin-jobs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=mighty_monk/linkedin-jobs-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Jobs Scraper", "description": "Scrape public LinkedIn job search results and job detail pages. Extract title, company, location, employment type, seniority, description, apply URL, posted date, and applicants info when public.", "version": "1.0", "x-build-id": "2k0YAXbWjEo9aSo1U" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/mighty_monk~linkedin-jobs-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-mighty_monk-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/mighty_monk~linkedin-jobs-scraper/runs": { "post": { "operationId": "runs-sync-mighty_monk-linkedin-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/mighty_monk~linkedin-jobs-scraper/run-sync": { "post": { "operationId": "run-sync-mighty_monk-linkedin-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "searchUrls": { "title": "LinkedIn job search URLs", "type": "array", "description": "One or more public LinkedIn job search URLs (e.g. https://www.linkedin.com/jobs/search/?keywords=software%20engineer&location=United%20States). The Actor converts these to guest API endpoints for scraping.", "default": [], "items": { "type": "string" } }, "keywords": { "title": "Keywords", "type": "string", "description": "Job search keywords used when building a search URL (if searchUrls is empty or in addition to searchUrls). Example: software engineer.", "default": "" }, "location": { "title": "Location", "type": "string", "description": "Location string paired with keywords (e.g. United States, Remote, San Francisco, CA).", "default": "" }, "maxJobs": { "title": "Max jobs", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum number of unique jobs to scrape (deduplicated by jobId).", "default": 50 }, "maxConcurrency": { "title": "Max concurrency", "minimum": 1, "maximum": 20, "type": "integer", "description": "Maximum number of concurrent HTTP requests. Keep low (1–3) to reduce LinkedIn rate limits and auth walls.", "default": 2 }, "maxRequestRetries": { "title": "Max request retries", "minimum": 0, "maximum": 10, "type": "integer", "description": "How many times to retry a failed HTTP request before giving up.", "default": 3 }, "requestDelayMs": { "title": "Request delay (ms)", "minimum": 0, "maximum": 30000, "type": "integer", "description": "Approximate delay between requests used to compute rate limiting (max requests per minute).", "default": 1000 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Apify Proxy settings. Strongly recommended for LinkedIn (residential often works better).", "default": { "useApifyProxy": true } }, "includeDescription": { "title": "Include job description", "type": "boolean", "description": "When true, visit each job detail page (guest jobPosting API) to extract full description, seniority, employment type, applicants, and apply URL.", "default": 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 } } } } } } } } } } ```