# LinkedIn Job Listings Scraper (`openclawai/linkedin-jobs-scraper-jobspy`) Actor Scrape LinkedIn jobs - Search by keyword, location, company, salary, posted-date, remote, easy-apply. Full descriptions, salary range, direct apply URLs. Multi-keyword search, auto-deduplication, pay only for results. No API key - **URL**: https://apify.com/openclawai/linkedin-jobs-scraper-jobspy.md - **Developed by:** [Pika Choo](https://apify.com/openclawai) (community) - **Categories:** Jobs, Lead generation, Integrations - **Stats:** 12 total users, 4 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 job scrapeds This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 Jobs Scraper Scrape LinkedIn job listings at **$0.005 per job** — search by keyword, location, company, posted-date, easy-apply and more. Pay only for results you receive. ### Features - **Cheap LinkedIn jobs scraping** — $0.005/job ($5 per 1,000 jobs) - **Multi-keyword search** — run up to 5 queries in one go, results merged and deduplicated - **Rich job data** — title, company, location, salary range, job type, remote flag, posted date, direct apply URL - **Full descriptions** — optional flag to fetch complete markdown/HTML descriptions per posting - **Targeted search** — filter by specific LinkedIn company IDs, distance radius, hours since posting, easy-apply, remote, job type - **Salary normalization** — auto-convert hourly/monthly pay to annual for easy comparison - **Pagination** — offset support for sweeping through large result sets - **Auto-deduplication** — same job listed twice is collapsed to one row - **Pay-per-result** — billed only on jobs returned in the dataset, never on failures - **Spending cap** — `ACTOR_MAX_TOTAL_CHARGE_USD` honored to prevent runaway cost ### Pricing | Event | Price | |---|---| | `job-scraped` | **$0.005** per job | 100 jobs → $0.50. 1,000 jobs → $5.00. 10,000 jobs → $50. ### Inputs | Field | Type | Description | |---|---|---| | `searchTerm` | string | Job title or keyword (e.g. `"software engineer"`) | | `searchTerms` | array (max 5) | Multiple OR-merged queries | | `location` | string | City, state, or country (e.g. `"New York, NY"`) | | `maxResults` | int (1–5000) | Max jobs per search term (default 100) | | `isRemote` | bool | Remote-only filter | | `jobType` | enum | fulltime / parttime / contract / internship / temporary | | `hoursOld` | int | Only jobs posted within last N hours | | `distance` | int | Search radius in miles | | `offset` | int | Skip first N results | | `easyApply` | bool | One-click apply jobs only | | `linkedinFetchDescription` | bool | Fetch full descriptions | | `linkedinCompanyIds` | array | Restrict to specific company IDs | | `descriptionFormat` | enum | `markdown` (default) or `html` | | `enforceAnnualSalary` | bool | Normalize salaries to annual | | `proxyConfiguration` | object | Apify proxy (residential recommended) | ### Output Each row contains: `title`, `company`, `location`, `job_url`, `job_url_direct`, `description`, `salary_min`, `salary_max`, `salary_currency`, `salary_interval`, `job_type`, `is_remote`, `date_posted`, `company_industry`, `company_logo`, `skills`, `experience_range`, `vacancy_count`, `work_from_home_type`, plus search metadata. ### Tips - Up to **5,000 jobs per search term**, **25,000 per run** (5 terms × 5,000). - For runs above 100 jobs, always use **residential proxies** — LinkedIn rate-limits IPs aggressively. - Large runs (>1,000 jobs) may take 10+ minutes; bump the run timeout to 3,600 s if needed. - LinkedIn may return fewer than requested — you're only charged for jobs actually delivered. - Combining `hoursOld` with `easyApply` is unsupported by LinkedIn; the scraper auto-drops `easyApply` and warns. - Set `ACTOR_MAX_TOTAL_CHARGE_USD` env var to cap spend per run. # Actor input Schema ## `searchTerm` (type: `string`): Job title, keyword, or skill to search for (e.g. "software engineer", "data analyst"). ## `searchTerms` (type: `array`): Run up to 5 queries in one go — results are merged and deduplicated. Each row is tagged with the term that surfaced it. Cost scales linearly. Leave empty to use the single Search Term above. ## `location` (type: `string`): City, state, or country (e.g. "New York, NY", "London", "Remote"). Leave empty to search globally. ## `maxResults` (type: `integer`): Maximum jobs to return per search term (1–5000). Runs above 100 require residential proxies — LinkedIn rate-limits IPs aggressively. Large runs (>1000) may take 10+ minutes. ## `isRemote` (type: `boolean`): Return only remote job listings. ## `jobType` (type: `string`): Filter by employment type. ## `hoursOld` (type: `integer`): Only return jobs posted within the last N hours (24 = last day, 168 = last week). Cannot be combined with Easy Apply. ## `distance` (type: `integer`): Search radius in miles from the location. Use 0 for exact location only. ## `offset` (type: `integer`): Skip the first N results — useful for paginating large result sets. ## `easyApply` (type: `boolean`): Return only one-click apply jobs. Cannot be combined with Posted Within. ## `linkedinFetchDescription` (type: `boolean`): Fetch the full job description and direct apply URL for each posting. Slower but richer output. ## `linkedinCompanyIds` (type: `array`): Restrict the search to specific companies by their LinkedIn company ID (e.g. ["1441", "2382910"]). Leave empty to search all companies. ## `descriptionFormat` (type: `string`): Format for description text in the output. ## `enforceAnnualSalary` (type: `boolean`): Convert hourly/monthly salaries to annual equivalents for easier comparison. ## `proxyConfiguration` (type: `object`): Residential proxies recommended — LinkedIn rate-limits IPs after ~100 results. ## Actor input object example ```json { "searchTerm": "software engineer", "location": "New York, NY", "maxResults": 100, "isRemote": false, "jobType": "", "distance": 50, "easyApply": false, "linkedinFetchDescription": false, "descriptionFormat": "markdown", "enforceAnnualSalary": false, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ```` # 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 = { "searchTerm": "software engineer", "location": "New York, NY" }; // Run the Actor and wait for it to finish const run = await client.actor("openclawai/linkedin-jobs-scraper-jobspy").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 = { "searchTerm": "software engineer", "location": "New York, NY", } # Run the Actor and wait for it to finish run = client.actor("openclawai/linkedin-jobs-scraper-jobspy").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 '{ "searchTerm": "software engineer", "location": "New York, NY" }' | apify call openclawai/linkedin-jobs-scraper-jobspy --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=openclawai/linkedin-jobs-scraper-jobspy", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Job Listings Scraper", "description": "Scrape LinkedIn jobs - Search by keyword, location, company, salary, posted-date, remote, easy-apply. Full descriptions, salary range, direct apply URLs. Multi-keyword search, auto-deduplication, pay only for results. No API key", "version": "1.0", "x-build-id": "5zIk3PcKmxcHiQsHK" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/openclawai~linkedin-jobs-scraper-jobspy/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-openclawai-linkedin-jobs-scraper-jobspy", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/openclawai~linkedin-jobs-scraper-jobspy/runs": { "post": { "operationId": "runs-sync-openclawai-linkedin-jobs-scraper-jobspy", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/openclawai~linkedin-jobs-scraper-jobspy/run-sync": { "post": { "operationId": "run-sync-openclawai-linkedin-jobs-scraper-jobspy", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchTerm": { "title": "Search Term", "type": "string", "description": "Job title, keyword, or skill to search for (e.g. \"software engineer\", \"data analyst\")." }, "searchTerms": { "title": "Multiple Search Terms", "maxItems": 5, "type": "array", "description": "Run up to 5 queries in one go — results are merged and deduplicated. Each row is tagged with the term that surfaced it. Cost scales linearly. Leave empty to use the single Search Term above.", "items": { "type": "string" } }, "location": { "title": "Location", "type": "string", "description": "City, state, or country (e.g. \"New York, NY\", \"London\", \"Remote\"). Leave empty to search globally." }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum jobs to return per search term (1–5000). Runs above 100 require residential proxies — LinkedIn rate-limits IPs aggressively. Large runs (>1000) may take 10+ minutes.", "default": 100 }, "isRemote": { "title": "Remote Jobs Only", "type": "boolean", "description": "Return only remote job listings.", "default": false }, "jobType": { "title": "Job Type", "enum": [ "", "fulltime", "parttime", "contract", "internship", "temporary" ], "type": "string", "description": "Filter by employment type.", "default": "" }, "hoursOld": { "title": "Posted Within (hours)", "minimum": 1, "maximum": 8760, "type": "integer", "description": "Only return jobs posted within the last N hours (24 = last day, 168 = last week). Cannot be combined with Easy Apply." }, "distance": { "title": "Search Radius (miles)", "minimum": 0, "maximum": 200, "type": "integer", "description": "Search radius in miles from the location. Use 0 for exact location only.", "default": 50 }, "offset": { "title": "Results Offset", "minimum": 0, "type": "integer", "description": "Skip the first N results — useful for paginating large result sets." }, "easyApply": { "title": "Easy Apply Only", "type": "boolean", "description": "Return only one-click apply jobs. Cannot be combined with Posted Within.", "default": false }, "linkedinFetchDescription": { "title": "Fetch Full Descriptions", "type": "boolean", "description": "Fetch the full job description and direct apply URL for each posting. Slower but richer output.", "default": false }, "linkedinCompanyIds": { "title": "Target Company IDs", "type": "array", "description": "Restrict the search to specific companies by their LinkedIn company ID (e.g. [\"1441\", \"2382910\"]). Leave empty to search all companies.", "items": { "type": "string" } }, "descriptionFormat": { "title": "Description Format", "enum": [ "markdown", "html" ], "type": "string", "description": "Format for description text in the output.", "default": "markdown" }, "enforceAnnualSalary": { "title": "Normalize to Annual Salary", "type": "boolean", "description": "Convert hourly/monthly salaries to annual equivalents for easier comparison.", "default": false }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Residential proxies recommended — LinkedIn rate-limits IPs after ~100 results.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "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 } } } } } } } } } } ```