# LinkedIn Scraper (`codingfrontend/linkedin-scraper`) Actor General LinkedIn scraper that can search for jobs, companies, people, and posts. Supports multiple search modes with full data extraction, pagination, and filtering. - **URL**: https://apify.com/codingfrontend/linkedin-scraper.md - **Developed by:** [codingfrontend](https://apify.com/codingfrontend) (community) - **Categories:** Jobs, Lead generation, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 1,000 results 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 Scraper (General) A versatile LinkedIn scraper that supports four search modes: **jobs**, **companies**, **people**, and **posts**. One actor for all your LinkedIn data needs. ### Features - Four search modes: jobs, companies, people, posts - Full pagination support for large result sets - Filters by location, date posted, and job type - Handles optional LinkedIn authentication for extended access - Unified output schema across all modes - Dataset views: **Overview** and **Full Details** ### Input Parameters | Parameter | Type | Required | Default | Description | |---|---|---|---|---| | `searchMode` | string | ✅ | `jobs` | `jobs`, `companies`, `people`, or `posts` | | `query` | string | ✅ | — | Search keywords (e.g. `"software engineer"`, `"Microsoft"`, `"AI trends"`) | | `location` | string | — | `United States` | Location filter (for jobs/people searches) | | `maxItems` | integer | — | `50` | Max items to scrape (1–500) | | `datePosted` | string | — | `anyTime` | `anyTime`, `pastMonth`, `pastWeek`, `past24Hours` | | `jobType` | string | — | any | `F` = Full-time, `P` = Part-time, `C` = Contract, `T` = Temporary, `I` = Internship | | `linkedinCookie` | string | — | — | LinkedIn `li_at` session cookie (required for people/companies/posts) | | `scrapeDetails` | boolean | — | `true` | Visit each result for full details | | `proxyConfiguration` | object | — | — | Proxy settings (residential recommended) | ### Search Mode Guide | Mode | Auth Required | What It Scrapes | |---|---|---| | `jobs` | No | Job listings via LinkedIn's public guest API | | `companies` | Recommended | Company search result cards | | `people` | Yes | Person search results (requires `li_at` cookie) | | `posts` | Yes | Content/post search results | ### Getting the LinkedIn Cookie 1. Log into LinkedIn in your browser 2. Open DevTools → Application → Cookies → `linkedin.com` 3. Copy the value of the `li_at` cookie 4. Paste it into the `linkedinCookie` input field ### Output Fields | Field | Type | Description | |---|---|---| | `type` | string | Result type: `job`, `company`, `person`, or `post` | | `title` | string | Job title, company name, person name, or post snippet | | `subtitle` | string | Company (for jobs), industry (companies), headline (people) | | `url` | string | LinkedIn URL for this result | | `location` | string | Location of the result | | `description` | string | Full description, about text, or post content | | `imageUrl` | string | Logo, profile photo, or post image | | `metadata` | object | Type-specific data (jobId, followers, likes, hashtags, etc.) | | `searchQuery` | string | Query that produced this result | | `searchMode` | string | The search mode used | | `scrapedAt` | string | ISO 8601 timestamp | ### Example Output — Jobs Mode ```json { "type": "job", "title": "Software Engineer", "subtitle": "Google", "url": "https://www.linkedin.com/jobs/view/...", "location": "Mountain View, CA", "metadata": { "jobId": "1234567890", "postedDate": "2026-05-10" }, "searchQuery": "software engineer", "searchMode": "jobs", "scrapedAt": "2026-05-12T22:43:58.494Z" } ```` ### Example Output — People Mode ```json { "type": "person", "title": "Jane Smith", "subtitle": "Senior Product Manager at Stripe", "url": "https://www.linkedin.com/in/jane-smith/", "location": "San Francisco, CA", "metadata": { "connectionDegree": "2nd" }, "searchQuery": "product manager", "searchMode": "people", "scrapedAt": "2026-05-12T22:43:58.494Z" } ``` ### Dataset Views - **Overview**: Type, title, subtitle, URL, location, search query, search mode, scraped date - **Full Details**: All overview fields + description, metadata, image URL ### Notes - Jobs mode uses LinkedIn's public API — no authentication needed - People, companies, and posts modes require a valid `li_at` session cookie - Residential proxies are strongly recommended for all modes - For focused scraping, use the dedicated scrapers: `linkedin-jobs-scraper`, `linkedin-company-scraper`, `linkedin-person-scraper`, `linkedin-post-search` # Actor input Schema ## `searchMode` (type: `string`): What to search for on LinkedIn. ## `query` (type: `string`): Search keywords. For jobs: 'software engineer', companies: 'Microsoft', people: 'John Doe', posts: 'AI trends'. ## `location` (type: `string`): Location filter (for jobs and people searches). E.g. 'United States', 'San Francisco, CA', 'Remote'. ## `maxItems` (type: `integer`): Maximum number of items to scrape. ## `datePosted` (type: `string`): Filter by when the job/post was published. ## `jobType` (type: `string`): Employment type filter. ## `linkedinCookie` (type: `string`): LinkedIn session cookie for accessing protected content (required for people/companies). ## `scrapeDetails` (type: `boolean`): Visit each result page for complete details. Slower but more data. ## `proxyConfiguration` (type: `object`): Proxy settings. Residential proxies strongly recommended for LinkedIn. ## Actor input object example ```json { "searchMode": "jobs", "query": "product manager", "location": "United States", "maxItems": 50, "datePosted": "anyTime", "jobType": "", "scrapeDetails": true, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # 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 = { "query": "software engineer", "location": "United States", "maxItems": 50, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("codingfrontend/linkedin-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 = { "query": "software engineer", "location": "United States", "maxItems": 50, "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("codingfrontend/linkedin-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 '{ "query": "software engineer", "location": "United States", "maxItems": 50, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call codingfrontend/linkedin-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=codingfrontend/linkedin-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Scraper", "description": "General LinkedIn scraper that can search for jobs, companies, people, and posts. Supports multiple search modes with full data extraction, pagination, and filtering.", "version": "1.0", "x-build-id": "T1bkp2P2u0QYXWBGA" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/codingfrontend~linkedin-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-codingfrontend-linkedin-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/codingfrontend~linkedin-scraper/runs": { "post": { "operationId": "runs-sync-codingfrontend-linkedin-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/codingfrontend~linkedin-scraper/run-sync": { "post": { "operationId": "run-sync-codingfrontend-linkedin-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "query", "searchMode" ], "properties": { "searchMode": { "title": "Search Mode", "enum": [ "jobs", "companies", "people", "posts" ], "type": "string", "description": "What to search for on LinkedIn.", "default": "jobs" }, "query": { "title": "Search Query / Keywords", "type": "string", "description": "Search keywords. For jobs: 'software engineer', companies: 'Microsoft', people: 'John Doe', posts: 'AI trends'." }, "location": { "title": "Location", "type": "string", "description": "Location filter (for jobs and people searches). E.g. 'United States', 'San Francisco, CA', 'Remote'.", "default": "United States" }, "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of items to scrape.", "default": 50 }, "datePosted": { "title": "Date Posted (for jobs/posts)", "enum": [ "anyTime", "pastMonth", "pastWeek", "past24Hours" ], "type": "string", "description": "Filter by when the job/post was published.", "default": "anyTime" }, "jobType": { "title": "Job Type (jobs mode only)", "enum": [ "", "F", "P", "C", "T", "I" ], "type": "string", "description": "Employment type filter.", "default": "" }, "linkedinCookie": { "title": "LinkedIn Cookie (li_at)", "type": "string", "description": "LinkedIn session cookie for accessing protected content (required for people/companies)." }, "scrapeDetails": { "title": "Scrape Full Details", "type": "boolean", "description": "Visit each result page for complete details. Slower but more data.", "default": true }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings. Residential proxies strongly recommended for LinkedIn." } } }, "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 } } } } } } } } } } ```