# Linkedin Profile BULK Scraper (`muhammad_usama/apify-person`) Actor Scrapes Linkedin.com Person data in Realtime. - **URL**: https://apify.com/muhammad\_usama/apify-person.md - **Developed by:** [Muhammad Usama](https://apify.com/muhammad_usama) (community) - **Categories:** Lead generation, Automation, Social media - **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.20 / 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.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 Bulk Scraper Extract detailed LinkedIn profile data at scale from public LinkedIn profile URLs. ### Overview LinkedIn Profile Bulk Scraper is designed for recruiters, sales teams, lead generation agencies, market researchers, and data enrichment workflows that need structured LinkedIn profile data in bulk. Simply provide a list of LinkedIn profile URLs and the Actor will process them automatically. #### Key Features * Process up to **1,000 LinkedIn profile URLs per run** * Bulk profile enrichment * Fast and reliable extraction * Structured JSON output * Pay only for successful results * Works with public LinkedIn profile URLs * Suitable for CRM enrichment and lead generation ### Pricing This Actor uses **Pay Per Result** pricing. **$1.20 per 1,000 successful results** You are charged only for profiles that are successfully processed. | Successful Profiles | Cost | | ------------------- | ------ | | 100 | $0.12 | | 500 | $0.60 | | 1,000 | $1.20 | | 10,000 | $12.00 | ### Input Provide an array of LinkedIn profile URLs. #### Example Input ```json { "links": [ "https://www.linkedin.com/in/williamhgates", "https://www.linkedin.com/in/ingmar-klein", "https://www.linkedin.com/in/satyanadella" ] } ```` ### Output For every successfully processed LinkedIn profile, the Actor returns a detailed JSON object containing profile information. #### Available Data ##### Profile Information - Full name - First name - Last name - Public identifier - Headline - About section - Industry - Location - Premium status - Creator status - Influencer status ##### Profile Images - Profile picture - Background picture - Multiple image dimensions - Image URLs ##### Work Experience - Company names - Job titles - Employment dates - Employment duration - Locations - Descriptions - Company URLs - Company logos ##### Education - Schools - Universities - Degrees - Educational descriptions ##### Skills - Professional skills - Endorsed skills ##### Certifications - Licenses - Certificates - Issuing organizations - Issue dates ##### Languages - Languages spoken - Proficiency levels ##### Organizations - Professional memberships - Communities - Associations ##### Awards & Honors - Awards - Recognitions - Achievements ##### Volunteer Experience - Volunteer roles - Community involvement ##### Projects - Professional projects ##### Interests - Interests and activities ### Example Output ```json { "item": "https://www.linkedin.com/in/williamhgates", "data": { "urn": "ACoAACeIPPkBUymOGNvgfbBL_uhKc32Hg_g_haU", "firstName": "Ingmar", "lastName": "Klein", "fullName": "Ingmar Klein", "publicIdentifier": "ingmar-klein", "headline": "CEO @ Huzzle", "about": "exploring my action space", "industry": "Computer Software", "addressCountryOnly": "United States", "addressWithCountry": "San Francisco Bay Area United States", "profilePic": "https://...", "premium": true, "creator": true, "experiences": [...], "educations": [...], "skills": [...], "languages": [...], "licenseAndCertificates": [...], "organizations": [...], "honorsAndAwards": [...], "volunteerAndAwards": [...], "projects": [], "interests": [] } } ``` ### Usage Examples #### Recruiting Enrich candidate profiles with: - Work history - Skills - Education - Certifications #### Lead Generation Build enriched prospect databases containing: - Professional titles - Company information - Industries - Locations #### CRM Enrichment Automatically populate CRM records with: - LinkedIn profile data - Employment history - Skills and qualifications #### Market Research Analyze: - Industry trends - Career paths - Company movements - Professional backgrounds ### Processing Limits - Up to **1,000 LinkedIn profiles per run** - Bulk processing supported - One result generated per successfully processed profile ### Result-Based Billing This Actor follows Apify's Pay Per Result model. A result is counted only when a LinkedIn profile is successfully processed and returned in the dataset. Failed, invalid, or inaccessible profiles are not billed. ### Notes - Input URLs should be valid LinkedIn profile URLs. - The Actor is optimized for large-scale profile enrichment workflows. - Processing time depends on the number of profiles submitted. - Charges apply only to successful results. ### Support If you encounter issues or need additional features, please open an issue through the Actor page or contact support. # Actor input Schema ## `links` (type: `array`): Feed body as json object according to selected endpoint. ## Actor input object example ```json { "links": [ "https://www.linkedin.com/in/ingmar-klein", "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 = { "links": [ "https://www.linkedin.com/in/ingmar-klein", "https://www.linkedin.com/in/williamhgates" ] }; // Run the Actor and wait for it to finish const run = await client.actor("muhammad_usama/apify-person").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 = { "links": [ "https://www.linkedin.com/in/ingmar-klein", "https://www.linkedin.com/in/williamhgates", ] } # Run the Actor and wait for it to finish run = client.actor("muhammad_usama/apify-person").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 '{ "links": [ "https://www.linkedin.com/in/ingmar-klein", "https://www.linkedin.com/in/williamhgates" ] }' | apify call muhammad_usama/apify-person --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=muhammad_usama/apify-person", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Linkedin Profile BULK Scraper", "description": "Scrapes Linkedin.com Person data in Realtime.", "version": "0.0", "x-build-id": "SXwJ5d8kP0Nq3BfS2" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/muhammad_usama~apify-person/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-muhammad_usama-apify-person", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/muhammad_usama~apify-person/runs": { "post": { "operationId": "runs-sync-muhammad_usama-apify-person", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/muhammad_usama~apify-person/run-sync": { "post": { "operationId": "run-sync-muhammad_usama-apify-person", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "links" ], "properties": { "links": { "title": "Body", "type": "array", "description": "Feed body as json object according to selected endpoint." } } }, "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 } } } } } } } } } } ```