# All in One LinkedIn Scraper (`scrapecraze/linkedin-scraper`) Actor LinkedIn Scraper extracts public LinkedIn profile data, including names, job titles, companies, locations, skills, education, experience, and profile URLs. Ideal for lead generation, recruitment, market research, sales prospecting, and data enrichment workflows. - **URL**: https://apify.com/scrapecraze/linkedin-scraper.md - **Developed by:** [ScrapeCraze](https://apify.com/scrapecraze) (community) - **Categories:** Lead generation, Jobs, 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 Profile Scraper 🎯 Manually visiting LinkedIn profiles and company pages to collect lead and company details is slow and doesn’t scale. **LinkedIn Profile Scraper** quickly pulls structured profile and company data from a list of public LinkedIn URLs, so you can move from research to outreach faster. If you’re looking for a LinkedIn profile scraper, LinkedIn lead scraper, or LinkedIn data extraction workflow, this is built for that. It’s especially useful for sales teams, recruiters, and researchers who need consistent LinkedIn profile scraping software output at scale—results can start appearing within seconds of launch in one run. --- ### See the Data: Sample Output Here's a real record from a single run: ```json { "full_name": "William H. Gates", "first_name": "William", "last_name": "H. Gates", "headline": "Technology and philanthropy", "summary": "Co-founder and philanthropist...", "country": "United States of America", "city": "Seattle", "profile_pic_url": "https://example.com/profile.jpg", "follower_count": 195000000, "public_identifier": "williamhgates", "open_to_work": false, "show_verification_badge": false, "skills": ["Leadership", "Software", "Philanthropy"], "certifications": ["Global Health Leadership Program"], "experiences": [ { "title": "Co-chair", "company": "Microsoft", "company_linkedin_profile_url": "https://www.linkedin.com/company/microsoft", "starts_at": "1994" } ], "education": [ { "school": "Harvard University", "school_linkedin_profile_url": "https://www.linkedin.com/school/harvard-university", "starts_at": "1973", "ends_at": "1975" } ], "background_cover_image_url": "https://example.com/cover.jpg", "languages": ["English"], "personal_emails": [], "personal_numbers": [], "company_name": "Microsoft", "company_industry": "Technology", "company_website": "https://www.microsoft.com", "company_linkedin": "https://www.linkedin.com/company/microsoft", "company_size": "N/A", "url": "https://www.linkedin.com/in/williamhgates", "id": "1", "error_message": null, "status": "success" } ```` | Field | Type | What It Tells You | |---|---|---| | `url` | string | The exact LinkedIn URL that was processed, useful for traceability | | `id` | string | The record identifier used in the output (either provided in input or an incremental index) | | `full_name` | string | The public display name for the profile | | `headline` | string | The profile headline from the page’s top card area (good for role and positioning) | | `summary` | string | The profile “About” text when available | | `country` | string | A cleaned country name derived from the page/address data | | `city` | string | The city associated with the person profile (cleaned for usability) | | `profile_pic_url` | string | The profile picture URL for visual enrichment | | `follower_count` | number | null | Estimated follower count when the page provides it | | `skills` | array | A list of skills detected on the profile page | | `experiences` | array | Work history items with titles, companies, and start years (when found) | | `education` | array | Education items including linked school profile URLs when available | | `company_name` | string | The current/first company from the experiences list (when present) | | `company_industry` | string | Company industry detected from page data (or fallback value) | | `personal_emails` | array | Email addresses the actor stores as “personal\_emails” (empty when not found) | | `personal_numbers` | array | Phone numbers detected and stored as “personal\_numbers” (empty when not found) | | `error_message` | string | null | Error details when something goes wrong (otherwise `null`) | | `status` | string | Indicates whether the record was successfully pushed | Export your full dataset as JSON, CSV, or Excel from the Apify dashboard. *** ### Setting It Up Drop this into your `input.json` and you're ready to go: ```json { "startUrls": [ "https://www.linkedin.com/in/williamhgates" ] } ``` | Parameter | Required | What It Does | |---|---|---| | `startUrls` | ✅ | List of LinkedIn profile or company URLs to scrape. You can provide plain URLs or objects that include `url` and `id`. ↳ Each entry is processed in order, and results are written as records when extraction completes. | *** ### What It Does LinkedIn Profile Scraper fetches LinkedIn pages from your provided `startUrls`, identifies whether each URL represents a person profile or a company page, and then pushes a structured JSON record to the output dataset. #### Scrapes person profiles and company pages For person URLs, it extracts public profile fields like `full_name`, `headline`, `summary`, location (`city`, `country`), images, and structured sections like `skills`, `experiences`, and `education`. For company URLs, it extracts company-focused fields such as `name`, `tagline`, `description`, headquarters (`hq`), and company sizing info. #### Produces structured, integration-ready JSON Every processed page becomes a consistent JSON object with clearly named keys like `experiences`, `education`, `skills`, and company metadata (`website`, `company_size`, `founded_year`, `specialities`). This makes LinkedIn profile data scraper output easier to import into a CRM, a spreadsheet, or an analysis pipeline. #### Uses your URL list with per-record identifiers If you pass an object with an `id` alongside a `url`, that value becomes the output `id`. If you pass a plain string URL, the actor uses an incremental index (starting from 1) as `id`. This helps when you’re running a LinkedIn URL scraper workflow and need stable identifiers for mapping results back to your source list. #### Works with proxy support for reliable scraping The actor includes proxy configuration support to improve reliability for scraping runs. When proxy routing is enabled, requests are sent through the proxy URL before parsing the page content. #### Handles authwalls and imperfect access gracefully If an authwall or login page is detected, the actor logs a warning and continues. Output may be partial or missing for those URLs, but the run won’t stop the entire batch—each URL is processed independently. LinkedIn Profile Scraper delivers fast, structured LinkedIn contact and company page data extraction so you can scale prospecting and research without manual copying. *** ### Why LinkedIn Profile Scraper? There are plenty of ways to pull data from LinkedIn—here’s why LinkedIn Profile Scraper stands out. #### Built for bulk URL inputs You provide a list of LinkedIn profile or company URLs via `startUrls`, and the actor processes them one by one, pushing results as it goes. That’s a practical fit for a LinkedIn lead scraper workflow where you want repeatable, consistent outputs per URL. #### Clean, predictable field names Whether you’re scraping a LinkedIn recruiter scraper use case or a LinkedIn company page scraper task, the actor outputs well-named fields such as `headline`, `summary`, `experiences`, `education`, and company `hq`. This reduces the cleanup work you’d otherwise do after exporting. #### Reliability-focused request execution The actor logs errors per URL and continues when a page can’t be fetched. If a page appears to be blocked by an authwall or shows a login prompt, it records that as a warning so you can review which inputs may need reprocessing. *** ### Real-World Use Cases **Sales teams** often start with a list of prospects and then need consistent profile details to enrich outreach. With LinkedIn Profile Scraper, they paste profile URLs into `startUrls`, run once, and get structured fields like `headline`, `skills`, and `experiences` ready for lead research—without copy-paste. **Recruiters and talent researchers** use LinkedIn data extraction to quickly build structured shortlists from multiple people. After scraping target profiles, they can filter and compare candidates using extracted `summary`, location (`city`, `country`), and experience history in `experiences`. **Marketing agencies** running prospecting scraper tasks need reliable, repeatable datasets across clients and campaigns. By scraping both person profiles and company pages, they can produce lead-oriented outputs (like `company_name`, `company_industry`) and company context (`tagline`, `specialities`) from the same run. **Data analysts and researchers** benefit when scraped data lands in consistent JSON records. LinkedIn profile extractor output with keys like `education`, `skills`, and `follower_count` makes it easier to analyze patterns across audiences and roles without rebuilding schemas manually. **Automation specialists** integrating scraping into a workflow can trigger the actor via the Apify platform and consume the dataset programmatically. That turns LinkedIn contact scraper results into downstream steps like enrichment, deduplication, or routing—built around the same output JSON shape. *** ### How to Run It No code required. Here's how to get your first results in under 5 minutes: 1. **Open the actor on Apify** Go to the Apify console and find **LinkedIn Profile Scraper**: https://console.apify.com. 2. **Enter your `startUrls`** Paste one or more public LinkedIn profile or company URLs into the `startUrls` field. 3. **Configure proxy settings (optional)** If you need proxy support for better reliability on bulk runs, enable the proxy configuration options provided in the Apify UI. 4. **Start the run** Launch the actor and watch the live logs as each URL is processed and pushed to the dataset. 5. **Open the Dataset tab** Review records as they appear in real time (each input URL can result in one output object). 6. **Export your results** Download your dataset as JSON, CSV, or Excel from the Apify dashboard. 7. **Iterate with new URL lists** Run again with expanded `startUrls` to keep your LinkedIn prospecting scraper data fresh. The whole setup takes under 5 minutes — results start appearing within seconds of launch. *** ### Export & Integration Options Once your data is collected, LinkedIn Profile Scraper fits directly into your existing workflow. You can download your dataset from the Apify dashboard in common formats like JSON, CSV, or Excel. This is ideal for marketers and analysts who want to review scraped LinkedIn profile data extraction results immediately. For automation and engineering workflows, you can also connect the actor output to downstream steps using Apify’s API and automation integrations (for example, Zapier/Make style workflows). If you have an integration in mind, you can consume the dataset records as they’re produced and continue processing them in your pipeline. *** ### Pricing LinkedIn Profile Scraper runs on Apify, which includes a **free tier** — no credit card needed to start. The free tier provides $5 platform credits on sign-up, enough for several real test runs. After that, usage is pay-as-you-go based on Apify Actor compute units (CU), without monthly fee lock-in. For heavier workloads, check Apify subscription plans and pricing details on the Apify pricing page. Start free at [apify.com](https://apify.com) — scale up when you need to. *** ### Reliability & Limitations | What We Handle | How | |---|---| | Rate-limited or blocked requests | Requests are executed with proxy support when enabled, improving scraping reliability | | Authwalls or login prompts | The actor detects login prompts/authwalls and logs a warning while continuing the run | | Failed page fetches | Errors are logged per URL and the actor continues to the next input | | Incremental progress | Each successful extraction is pushed to the dataset as it’s processed | Limitations: LinkedIn Profile Scraper works on pages accessible from public web data, and results can be partial when pages show authwalls or login-gated content. It’s not a substitute for authenticated access to private or restricted profile sections. For enterprise-scale needs or custom configurations, reach out and we’ll help. *** ### Frequently Asked Questions #### Is there a free plan? Yes, Apify provides a free tier with credits on sign-up, which is typically enough for several real test runs. #### Do I need to log in or create an account on LinkedIn? No. This LinkedIn profile scraper is designed to work with publicly accessible page content based on the URLs you provide. #### How accurate is the extracted data? Accuracy depends on what’s publicly available on the LinkedIn page at the time of scraping. Fields are extracted from the page content (and associated structured data) and may be missing when the page doesn’t expose that information. #### How many results can I get per run? Your results depend on how many items you include in `startUrls`. There isn’t an extra “maxResults” field in the actor input schema—so the number of outputs is driven by the number of URLs you submit. #### How fresh is the data? The data freshness matches the time of the run: each URL is fetched when processed, so the output reflects what was visible at that moment. #### Is this legal? Does it comply with GDPR / CCPA? The actor processes **publicly available data** visible on the pages you provide. Compliance with GDPR, CCPA, and any relevant platform terms is your responsibility when using, storing, or sharing the resulting dataset. #### Can I export to Google Sheets or Excel? Yes. You can export your dataset from the Apify dashboard as JSON, CSV, or Excel, then import it into Google Sheets or your preferred spreadsheet tool. #### Can I schedule this to run automatically? Yes. You can use Apify’s platform scheduling features to run the actor automatically on a schedule, depending on your Apify setup. #### Can I access results via the API? Yes. You can trigger runs programmatically and retrieve results using Apify’s API, using the dataset produced by the run. #### What happens when the actor encounters an error? If a page can’t be fetched or processed, the actor logs the error for that URL and continues with the remaining inputs. If an authwall or login prompt is detected, it logs a warning and the record may be partial. *** ### Get Help & Use Responsibly Got a question about LinkedIn Profile Scraper or a feature you'd like added? Reach out at — we respond and actively maintain this actor based on user feedback. If you want ideas, tell us what you’d like to improve next—such as keyword-based filtering of profiles, or exporting additional fields in a format that fits your CRM schema. **LinkedIn Profile Scraper uses publicly available data** and does not access private accounts, login-gated pages, or password-protected content. You’re responsible for ensuring GDPR, CCPA, and LinkedIn’s Terms of Service compliance when you store and use the extracted data. For data removal requests, contact . Use responsibly, ethically, and only for lawful purposes. # Actor input Schema ## `startUrls` (type: `array`): List of LinkedIn profile or company URLs to scrape. ## Actor input object example ```json { "startUrls": [ { "url": "https://www.linkedin.com/in/williamhgates" } ] } ``` # 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 = { "startUrls": [ { "url": "https://www.linkedin.com/in/williamhgates" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapecraze/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 = { "startUrls": [{ "url": "https://www.linkedin.com/in/williamhgates" }] } # Run the Actor and wait for it to finish run = client.actor("scrapecraze/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 '{ "startUrls": [ { "url": "https://www.linkedin.com/in/williamhgates" } ] }' | apify call scrapecraze/linkedin-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapecraze/linkedin-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "All in One LinkedIn Scraper", "description": "LinkedIn Scraper extracts public LinkedIn profile data, including names, job titles, companies, locations, skills, education, experience, and profile URLs. Ideal for lead generation, recruitment, market research, sales prospecting, and data enrichment workflows.", "version": "1.0", "x-build-id": "pd3gCGnMo8GDyxJXN" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapecraze~linkedin-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapecraze-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapecraze~linkedin-scraper/runs": { "post": { "operationId": "runs-sync-scrapecraze-linkedin-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapecraze~linkedin-scraper/run-sync": { "post": { "operationId": "run-sync-scrapecraze-linkedin-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "startUrls" ], "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "List of LinkedIn profile or company URLs to scrape.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } } } }, "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 } } } } } } } } } } ```