# LinkedIn Company Details Scraper (`khadinakbar/linkedin-company-details-scraper`) Actor Scrape full LinkedIn company firmographics by URL or slug — industry, size, employees, funding, HQ. Cookieless, MCP-ready. - **URL**: https://apify.com/khadinakbar/linkedin-company-details-scraper.md - **Developed by:** [Khadin Akbar](https://apify.com/khadinakbar) (community) - **Categories:** Lead generation, MCP servers - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 1,000 company scrapeds 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 Details Scraper Scrape **full LinkedIn company firmographics** from a company URL or slug — no login, no cookies. Give it `shopify` (or `https://www.linkedin.com/company/shopify`) and get back industry, company size, employee count, followers, headquarters, founded year, company type, specialties, funding history, logo, cover image, similar pages, sample employees, and (optionally) recent company posts — as one flat, agent-friendly JSON record. Built for AI agents and data teams: one URL in, one structured record out. MCP-ready. ### What you get | Field | Description | |---|---| | `companyName` | Company display name | | `linkedinUrl` | Canonical LinkedIn company URL | | `companyId` | LinkedIn numeric company ID | | `handle` | LinkedIn slug (e.g. `shopify`) | | `slogan` | Tagline shown on the page | | `description` | Full "About" text | | `industry` | Industry category (e.g. `Software Development`) | | `companySize` | Size band (e.g. `10,001+ employees`) | | `employeeCount` | Employees listed on LinkedIn (integer) | | `followers` | LinkedIn follower count (integer) | | `founded` | Year founded (integer) | | `headquarters` | HQ string | | `location` | `{ city, state, country }` | | `website` | Company website | | `type` | e.g. `Public Company`, `Privately Held` | | `specialties` | Array of specialty tags | | `logo` / `coverImage` | Image URLs | | `funding` | `{ numberOfRounds, lastRound{type,date,amount}, investors[] }` | | `similarPages` | Related company pages `[{ name, linkedinUrl }]` | | `sampleEmployees` | Notable employees `[{ name, title, profileUrl }]` | | `recentPosts` | (optional) `[{ url, datePublished, text }]` | | `source` | Which provider served the record | | `scrapedAt` | ISO 8601 timestamp | Empty/unknown fields are omitted (never `null`), so records stay compact. ### When to use this - Enrich a known list of companies with firmographics for B2B sales, ABM, or CRM hygiene. - Pull funding + size signals for market and competitor research. - Feed an AI agent that needs structured company facts from a LinkedIn URL. **Not for:** discovering companies by keyword (use **[linkedin-company-search-scraper](https://apify.com/khadinakbar/linkedin-company-search-scraper)**), employee rosters (**linkedin-company-employee-scraper**), company post feeds (**linkedin-company-posts-scraper**), or personal profiles (**linkedin-profile-details-scraper**). ### Input ```json { "companyUrls": ["https://www.linkedin.com/company/shopify", "stripe"], "includePosts": false, "maxCompanies": 100, "preferredProvider": "auto" } ```` | Field | Type | Default | Notes | |---|---|---|---| | `companyUrls` | string\[] | — (required) | Full company URLs or bare slugs. Profile/post URLs are rejected. | | `includePosts` | boolean | `false` | Add a `recentPosts` array per company. | | `maxCompanies` | integer | `100` | 1–1000. Caps work and spend. | | `preferredProvider` | string | `auto` | `auto` (ScrapeCreators → SociaVault fallback), `scrapecreators`, or `sociavault`. | ### Output One dataset record per company, plus a `RUN_SUMMARY` key-value record with run counters (`companiesScraped`, `notFound`, `providerErrors`, `estimatedCostUsd`). ```json { "companyName": "Shopify", "linkedinUrl": "https://www.linkedin.com/company/shopify", "industry": "Software Development", "companySize": "10,001+ employees", "employeeCount": 29084, "followers": 1092578, "founded": 2006, "headquarters": "Ottawa, ON", "website": "https://www.shopify.com", "type": "Public Company", "specialties": ["ecommerce", "API", "POS", "Payments"], "funding": { "numberOfRounds": 4, "lastRound": { "type": "Series C", "amount": "US$ 100.0M" } }, "source": "scrapecreators", "scrapedAt": "2026-06-27T00:00:00.000Z" } ``` ### Pricing Pay-per-event: - **$0.00005** per actor start - **$0.01** per company successfully scraped A 100-company run costs about **$1.00**. You are only charged for companies that return data — not-found slugs and invalid inputs are free. ### Reliability - **Dual provider with automatic fallback.** ScrapeCreators is primary; SociaVault is the fallback (order configurable). If one provider errors, the other is tried before the company is skipped. - **Honest results.** A company that does not exist is skipped gracefully (run still succeeds). The run only fails if *every* request hit a provider outage and nothing was returned. - **No login or cookies.** Returns only publicly available company-page data. ### Use via API / MCP ```bash curl -X POST "https://api.apify.com/v2/acts/khadinakbar~linkedin-company-details-scraper/runs?token=YOUR_TOKEN" \ -H "Content-Type: application/json" \ -d '{"companyUrls":["shopify","stripe"]}' ``` Exposed in the Apify MCP server as `apify--linkedin-company-details-scraper` — agents pass a company URL and receive the structured record directly. ### Related actors Part of the LinkedIn data cluster: `linkedin-company-search-scraper`, `linkedin-company-employee-scraper`, `linkedin-company-posts-scraper`, `linkedin-profile-details-scraper`, `linkedin-jobs-scraper`. ### Legal This actor returns only publicly available data from LinkedIn company pages. Use it in compliance with LinkedIn's Terms of Service and all applicable laws (including GDPR/CCPA). You are responsible for how you collect and use the data. No login-gated or private data is accessed. # Actor input Schema ## `companyUrls` (type: `array`): List of LinkedIn company pages to scrape. Each item is either a full company URL (e.g. 'https://www.linkedin.com/company/shopify') or a bare company slug (e.g. 'shopify'). Defaults to none — at least one is required. NOT for personal profiles, posts, or schools; use the matching profile/posts actor for those. ## `includePosts` (type: `boolean`): When true, each company record includes a 'recentPosts' array (post URL, date, text) published by the company page. Defaults to false to keep records small and cheap for AI agents. Does NOT change the per-company price. ## `maxCompanies` (type: `integer`): Hard ceiling on how many companies to scrape this run, after de-duplication. Accepts 1 to 1000. Defaults to 100. Caps both work and PPE spend — extra input URLs beyond this limit are ignored. ## `preferredProvider` (type: `string`): Which backend to try first. 'auto' (default) uses ScrapeCreators first and falls back to SociaVault on failure. 'sociavault' tries SociaVault first then ScrapeCreators. Both return the same normalized fields; this only changes order. Leave as 'auto' unless one provider is degraded. ## Actor input object example ```json { "companyUrls": [ "https://www.linkedin.com/company/microsoft" ], "includePosts": false, "maxCompanies": 100, "preferredProvider": "auto" } ``` # Actor output Schema ## `companies` (type: `string`): One record per LinkedIn company with full firmographics. ## `runSummary` (type: `string`): Counters for this run (scraped, not found, errors, cost). # 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/shopify", "stripe" ] }; // Run the Actor and wait for it to finish const run = await client.actor("khadinakbar/linkedin-company-details-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/shopify", "stripe", ] } # Run the Actor and wait for it to finish run = client.actor("khadinakbar/linkedin-company-details-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/shopify", "stripe" ] }' | apify call khadinakbar/linkedin-company-details-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=khadinakbar/linkedin-company-details-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Company Details Scraper", "description": "Scrape full LinkedIn company firmographics by URL or slug — industry, size, employees, funding, HQ. Cookieless, MCP-ready.", "version": "0.1", "x-build-id": "1GpxTnqw4ph0awX8q" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/khadinakbar~linkedin-company-details-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-khadinakbar-linkedin-company-details-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/khadinakbar~linkedin-company-details-scraper/runs": { "post": { "operationId": "runs-sync-khadinakbar-linkedin-company-details-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/khadinakbar~linkedin-company-details-scraper/run-sync": { "post": { "operationId": "run-sync-khadinakbar-linkedin-company-details-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "LinkedIn company URLs or slugs", "type": "array", "description": "List of LinkedIn company pages to scrape. Each item is either a full company URL (e.g. 'https://www.linkedin.com/company/shopify') or a bare company slug (e.g. 'shopify'). Defaults to none — at least one is required. NOT for personal profiles, posts, or schools; use the matching profile/posts actor for those.", "items": { "type": "string" } }, "includePosts": { "title": "Include recent company posts", "type": "boolean", "description": "When true, each company record includes a 'recentPosts' array (post URL, date, text) published by the company page. Defaults to false to keep records small and cheap for AI agents. Does NOT change the per-company price.", "default": false }, "maxCompanies": { "title": "Max companies", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Hard ceiling on how many companies to scrape this run, after de-duplication. Accepts 1 to 1000. Defaults to 100. Caps both work and PPE spend — extra input URLs beyond this limit are ignored.", "default": 100 }, "preferredProvider": { "title": "Preferred data provider", "enum": [ "auto", "scrapecreators", "sociavault" ], "type": "string", "description": "Which backend to try first. 'auto' (default) uses ScrapeCreators first and falls back to SociaVault on failure. 'sociavault' tries SociaVault first then ScrapeCreators. Both return the same normalized fields; this only changes order. Leave as 'auto' unless one provider is degraded.", "default": "auto" } } }, "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 } } } } } } } } } } ```