# LinkedIn Company Employees Scraper (`seemuapps/linkedin-company-employees-scraper`) Actor Extract employees from any public LinkedIn company page. One row per employee with name, headline, profile URL, and company context for lead generation. - **URL**: https://apify.com/seemuapps/linkedin-company-employees-scraper.md - **Developed by:** [Andrew](https://apify.com/seemuapps) (community) - **Categories:** Jobs, Lead generation, E-commerce - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 1,000 employee returneds 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 Company Employees Scraper Extract employees from any public LinkedIn company page — one row per employee with name, headline, profile URL, and company context. Built for lead generation, recruiting, and competitor research. ### What you get For every employee visible on a company's LinkedIn page, the scraper returns one row with: **Employee data** - Full name - Headline / current job title - LinkedIn profile URL - Profile picture URL **Company context columns** (joined onto every employee row) - Company name, LinkedIn URL, and public slug - Company website - Headquarters, country code - Industries, company size (e.g. "501-1,000 employees") - Total followers and total employees on LinkedIn - Year founded - Company logo URL Output is flat — one employee per record — so it exports cleanly to CSV, Google Sheets, or any CRM. ### Use cases - **B2B lead generation** — pull the team list of a target company and route leads to sales - **Recruiting** — find candidates already working at a competitor or talent-rich company - **Account-based marketing** — enrich your CRM with company-and-people data in one shot - **Competitive intelligence** — track hiring patterns, team composition, and headcount growth - **Investor research** — quickly map out a portfolio company's leadership team ### How to use 1. Paste one or more LinkedIn company page URLs into **Company URLs** (one per line; up to 20 per run) 2. Run the actor — employees appear in the **Dataset** tab, one per row 3. Export to JSON, CSV, or Google Sheets directly from the Apify console ### Output format Each dataset record: ```json { "employeeName": "Jane Doe", "employeeHeadline": "Software Engineer at Anthropic", "employeeProfileUrl": "https://www.linkedin.com/in/janedoe", "employeeImageUrl": "https://media.licdn.com/dms/image/...", "companyName": "Anthropic", "companyUrl": "https://www.linkedin.com/company/anthropicresearch", "companySlug": "anthropicresearch", "companyId": "61907786", "companyWebsite": "https://www.anthropic.com", "companyHeadquarters": "San Francisco, California", "companyCountryCode": "US", "companyIndustries": "Research Services", "companySize": "501-1,000 employees", "companyFollowers": 850000, "companyEmployeesOnLinkedIn": 720, "companyFounded": "2021", "companyLogo": "https://media.licdn.com/dms/image/..." } ```` ### Notes - Returns the employees that LinkedIn publishes on the company's public "People" widget (typically up to ~25 per company) - Each row is enriched with company-level fields, so a single export is everything you need to import into a CRM - Bulk mode: drop in up to 20 company URLs per run to enrich many accounts in one shot # Actor input Schema ## `companyURLs` (type: `array`): List of LinkedIn company page URLs. One URL per line. Maximum 20 per run. ## Actor input object example ```json { "companyURLs": [ "https://www.linkedin.com/company/anthropicresearch", "https://www.linkedin.com/company/openai" ] } ``` # Actor output Schema ## `results` (type: `string`): Each record contains: employeeName, employeeHeadline, employeeProfileUrl, employeeImageUrl, plus company context columns (companyName, companyUrl, companySlug, companyWebsite, companyHeadquarters, companyCountryCode, companyIndustries, companySize, companyFollowers, companyEmployeesOnLinkedIn, companyFounded, companyLogo). One row per employee — exports clean to CSV or Google Sheets. # 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 = { "companyURLs": [ "https://www.linkedin.com/company/anthropicresearch", "https://www.linkedin.com/company/openai" ] }; // Run the Actor and wait for it to finish const run = await client.actor("seemuapps/linkedin-company-employees-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 = { "companyURLs": [ "https://www.linkedin.com/company/anthropicresearch", "https://www.linkedin.com/company/openai", ] } # Run the Actor and wait for it to finish run = client.actor("seemuapps/linkedin-company-employees-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 '{ "companyURLs": [ "https://www.linkedin.com/company/anthropicresearch", "https://www.linkedin.com/company/openai" ] }' | apify call seemuapps/linkedin-company-employees-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seemuapps/linkedin-company-employees-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Company Employees Scraper", "description": "Extract employees from any public LinkedIn company page. One row per employee with name, headline, profile URL, and company context for lead generation.", "version": "1.0", "x-build-id": "erHk1stkqkITsho6Z" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seemuapps~linkedin-company-employees-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seemuapps-linkedin-company-employees-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/seemuapps~linkedin-company-employees-scraper/runs": { "post": { "operationId": "runs-sync-seemuapps-linkedin-company-employees-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/seemuapps~linkedin-company-employees-scraper/run-sync": { "post": { "operationId": "run-sync-seemuapps-linkedin-company-employees-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "companyURLs" ], "properties": { "companyURLs": { "title": "Company URLs", "type": "array", "description": "List of LinkedIn company page URLs. One URL per line. Maximum 20 per run.", "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```