# LinkedIn Profile Pro - Profile + Posts + Articles, No Cookies (`constructive_calm/linkedin-profile-pro`) Actor Scrape LinkedIn profiles in depth — name, headline, country, work history with dates, education with dates, recent posts with full text + likes, and published articles — all in one call. No cookies, no login required. - **URL**: https://apify.com/constructive\_calm/linkedin-profile-pro.md - **Developed by:** [Omar Eldeeb](https://apify.com/constructive_calm) (community) - **Categories:** Lead generation, Social media, Other - **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 2 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing $4.00 / 1,000 linkedin profile resolveds 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 Pro Deep, cookie-free LinkedIn profile scraper. Hand it profile URLs (or bare slugs), get back full profile metadata **plus** recent posts **plus** published articles — in a single call, in one dataset row per profile. Built for Clay, n8n, and Make pipelines where you currently have to call two or three separate actors to assemble the same picture. --- ### What you get per profile ```jsonc { "url": "https://www.linkedin.com/in/williamhgates/", "slug": "williamhgates", "name": "Bill Gates", "headline": "Creator, Top Voice", "about": "Co-chair of the Bill & Melinda Gates Foundation...", "photoUrl": "https://media.licdn.com/...", "country": "US", "city": "Seattle, Washington, United States", "followers": 40000000, "connections": 8, "workHistory": [ { "company": "Gates Foundation", "companyLinkedInUrl": "...", "title": null, "description": null, "location": null, "startDate": "2000", "endDate": null, "isCurrent": true }, { "company": "Breakthrough Energy", "startDate": "2015", "isCurrent": true, ... }, { "company": "Microsoft", "startDate": "1975", "isCurrent": true, ... } ], "education": [ { "school": "Harvard University", "startYear": 1973, "endYear": 1975 } ], "languages": [], "awards": [], "externalLinks": [], "recentPosts": [ { "urn": "7464707901635395584", "url": "https://www.linkedin.com/posts/williamhgates_...", "text": "I felt so powerless and scared when my dad was diagnosed with Alzheimer's...", "postedAt": "2026-05-25T03:10:26.346Z", "likes": 1765, "comments": 84, "shares": null, "isArticle": false, "headline": null } // up to ~10 recent posts per profile ], "publishedArticles": [ { "url": "https://www.linkedin.com/pulse/every-year-2-million-...", "title": "Every year, 2 million babies are stillborn.", "datePublished": "2026-05-02T00:35:55.000+00:00", "description": "A simple retinal scanner can change that." } // up to ~10 articles per profile (when published) ], "fetchedAt": "2026-05-26T15:20:00.000Z", "source": { "htmlSize": 613470, "proxyGroup": "DATACENTER", "attemptsRequired": 1, "uaUsed": "facebookexternalhit" } } ```` *** ### Input | Field | Type | Default | Notes | |---|---|---|---| | `profileUrls` | string\[] | **required** | Full LinkedIn URLs or bare slugs. Both work. `https://uk.linkedin.com/in/...` URLs accepted. `/company/`, `/jobs/`, non-LinkedIn URLs rejected silently. | | `includeRecentPosts` | boolean | `true` | Extract up to ~10 recent posts per profile. Bundled in same charge. | | `includeArticles` | boolean | `true` | Extract LinkedIn-published articles. Bundled in same charge. | | `enrichEngagementFromDom` | boolean | `true` | Parse comment + share counts (post `likes` already come from JSON-LD). Negligible cost. | | `postedAfter` | string | — | Drop posts/articles older than this date. Accepts `YYYY-MM-DD` or full ISO 8601 timestamp. Leave empty for no lower bound. | | `postedBefore` | string | — | Drop posts/articles newer than this date. Same format as `postedAfter`. Pair both for a between-range filter. Undated items are dropped when any date filter is active. | | `maxRetriesPerProfile` | integer | `5` | Fresh-IP attempts per profile. 1-10. | | `useResidentialFallback` | boolean | `false` | After 3 datacenter failures, retry via Apify residential proxy. Boosts success ~70% → ~85%. Adds ~$5/1K cost on stubborn profiles only. | | `concurrency` | integer | `5` | Parallel profile fetches. 1-20. | | `maxItems` | integer | `500` | Hard cap on profiles processed. | | `proxyConfiguration` | object | Apify datacenter `BUYPROXIES94952` | Override only if you have a specific reason — datacenter is the validated optimum (cheaper AND higher success rate than residential for this surface). | *** ### Pricing **$0.004 per profile resolved.** That's it. Recent posts and articles bundled — no per-post charge. - First **10 profiles per run are FREE** (per-run trial — useful for testing). - **No charge** for invalid slugs, soft-blocks, or empty responses. - **No charge** for duplicate inputs (we dedupe upfront). - Charge only fires when a Person JSON-LD block has been successfully parsed. Compare with the alternative on the Store: profile scraper at $4/1K + profile-posts at $2/1K = $6/1K bundled. This one is **$4/1K bundled**, in one call, one dataset row, one charge. *** ### How it works (high-level) LinkedIn whitelists social-link-preview bots (`facebookexternalhit/1.1`, `Twitterbot/1.0`) and serves them rich server-rendered HTML with structured JSON-LD blocks: `Person`, `DiscussionForumPosting`, `Article`. We fetch each profile with that UA via Apify's datacenter proxy, parse the JSON-LD, augment with DOM-extracted engagement counts (comments, shares), and emit a normalized row. When a profile resists datacenter IPs (rotating residential block-lists land on Apify's pool), the optional residential fallback kicks in after 3 failures. Soft-block detection is byte-precise (LinkedIn's "we noticed unusual activity" template is exactly 317,547 bytes), so we never mistake it for a real 200. No cookies, no login, no LinkedIn account, no Voyager API impersonation. Public data only. *** ### Common use cases - **Clay/n8n/Make enrichment pipelines** — pipe a list of LinkedIn URLs in, get full profiles + recent activity out. - **B2B prospecting with context** — beyond just name+title, see what they've posted recently to personalize outreach. - **Investor / hedge fund headcount tracking** — re-run periodically, diff `workHistory[].isCurrent` to detect hires and exits. - **Competitive intel on key people** — track posts + articles to monitor what competitors' execs are talking about. - **Recruiting research** — surface candidates' recent activity, not just their static resume. *** ### What's NOT included (cookie-free limits) - **Skills, certifications, volunteer, recommendations** — these sections aren't in the cookie-free JSON-LD. Add them in v0.2 if there's demand (DOM-extractable). - **Per-reaction breakdown** (like vs love vs celebrate) — only total likes available. - **Comment thread bodies** — only comment counts (auth-walled bodies). - **Sales Navigator, Recruiter, full activity history** — separate auth-scope, out of scope. - **Per-position job titles** — for some profiles LinkedIn doesn't include per-`worksFor` titles in the JSON-LD. You'll see `title: null` even when the company is present. Profile-side limitation. Expect ~70% success rate at default settings (~85% with residential fallback enabled). Failed profiles are NOT charged. *** ### License MIT — use the data within LinkedIn's Terms of Service and applicable scraping law (hiQ v. LinkedIn covers public data; this actor never touches authenticated surfaces). # Actor input Schema ## `profileUrls` (type: `array`): Paste full LinkedIn profile URLs (https://www.linkedin.com/in/) or just the slugs. Both work — we auto-normalize. ## `includeRecentPosts` (type: `boolean`): Extract up to ~10 recent posts per profile (full text, date, like count, post URL). Bundled with profile in same charge — no extra cost. ## `includeArticles` (type: `boolean`): Extract LinkedIn-published articles in addition to recent posts. Bundled — no extra cost. ## `enrichEngagementFromDom` (type: `boolean`): Parse comment and share counts from HTML markup (post likes already come from JSON-LD). Negligible extra cost. ## `postedAfter` (type: `string`): Drop posts/articles older than this date. Accepts YYYY-MM-DD or full ISO 8601 timestamp. Leave empty for no lower bound. Pair with 'postedBefore' for a between-range filter. ## `postedBefore` (type: `string`): Drop posts/articles newer than this date. Accepts YYYY-MM-DD or full ISO 8601 timestamp. Leave empty for no upper bound. ## `maxRetriesPerProfile` (type: `integer`): How many fresh-IP attempts before giving up on a profile. Higher = more reliable but more proxy spend. 5 is the validated sweet spot. ## `useResidentialFallback` (type: `boolean`): After 3 datacenter failures, retry via Apify residential proxy. Increases success rate to ~85-90% but adds ~$5/1K cost on failed profiles only. Recommended for stubborn profiles. ## `concurrency` (type: `integer`): Parallel profile fetches. Higher = faster but more 429 risk. 5 is the validated sweet spot. ## `maxItems` (type: `integer`): Hard cap on profiles processed in this run. Protects against runaway input. ## `proxyConfiguration` (type: `object`): Apify datacenter proxy (BUYPROXIES94952) is the validated optimum for cookie-free LinkedIn — 8x cheaper than residential at higher success rate. Override only if you have a specific reason. ## Actor input object example ```json { "profileUrls": [ "https://www.linkedin.com/in/williamhgates/", "https://www.linkedin.com/in/satyanadella/", "https://www.linkedin.com/in/simonsinek/" ], "includeRecentPosts": true, "includeArticles": true, "enrichEngagementFromDom": true, "maxRetriesPerProfile": 5, "useResidentialFallback": false, "concurrency": 5, "maxItems": 500, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "BUYPROXIES94952" ] } } ``` # Actor output Schema ## `results` (type: `string`): All extracted profile rows incl. work history, education, recent posts, and articles. ## `resultsCsv` (type: `string`): Same dataset as CSV. # 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 = { "profileUrls": [ "https://www.linkedin.com/in/williamhgates/", "https://www.linkedin.com/in/satyanadella/", "https://www.linkedin.com/in/simonsinek/" ] }; // Run the Actor and wait for it to finish const run = await client.actor("constructive_calm/linkedin-profile-pro").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 = { "profileUrls": [ "https://www.linkedin.com/in/williamhgates/", "https://www.linkedin.com/in/satyanadella/", "https://www.linkedin.com/in/simonsinek/", ] } # Run the Actor and wait for it to finish run = client.actor("constructive_calm/linkedin-profile-pro").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 '{ "profileUrls": [ "https://www.linkedin.com/in/williamhgates/", "https://www.linkedin.com/in/satyanadella/", "https://www.linkedin.com/in/simonsinek/" ] }' | apify call constructive_calm/linkedin-profile-pro --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=constructive_calm/linkedin-profile-pro", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Profile Pro - Profile + Posts + Articles, No Cookies", "description": "Scrape LinkedIn profiles in depth — name, headline, country, work history with dates, education with dates, recent posts with full text + likes, and published articles — all in one call. No cookies, no login required.", "version": "0.1", "x-build-id": "1qyGLz8zjCbMTIDyZ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/constructive_calm~linkedin-profile-pro/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-constructive_calm-linkedin-profile-pro", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/constructive_calm~linkedin-profile-pro/runs": { "post": { "operationId": "runs-sync-constructive_calm-linkedin-profile-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/constructive_calm~linkedin-profile-pro/run-sync": { "post": { "operationId": "run-sync-constructive_calm-linkedin-profile-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "profileUrls" ], "properties": { "profileUrls": { "title": "LinkedIn profile URLs or slugs", "type": "array", "description": "Paste full LinkedIn profile URLs (https://www.linkedin.com/in/) or just the slugs. Both work — we auto-normalize.", "items": { "type": "string" } }, "includeRecentPosts": { "title": "Include recent posts", "type": "boolean", "description": "Extract up to ~10 recent posts per profile (full text, date, like count, post URL). Bundled with profile in same charge — no extra cost.", "default": true }, "includeArticles": { "title": "Include published articles", "type": "boolean", "description": "Extract LinkedIn-published articles in addition to recent posts. Bundled — no extra cost.", "default": true }, "enrichEngagementFromDom": { "title": "Enrich engagement counts", "type": "boolean", "description": "Parse comment and share counts from HTML markup (post likes already come from JSON-LD). Negligible extra cost.", "default": true }, "postedAfter": { "title": "Posts published on or after", "type": "string", "description": "Drop posts/articles older than this date. Accepts YYYY-MM-DD or full ISO 8601 timestamp. Leave empty for no lower bound. Pair with 'postedBefore' for a between-range filter." }, "postedBefore": { "title": "Posts published on or before", "type": "string", "description": "Drop posts/articles newer than this date. Accepts YYYY-MM-DD or full ISO 8601 timestamp. Leave empty for no upper bound." }, "maxRetriesPerProfile": { "title": "Max retries per profile", "minimum": 1, "maximum": 10, "type": "integer", "description": "How many fresh-IP attempts before giving up on a profile. Higher = more reliable but more proxy spend. 5 is the validated sweet spot.", "default": 5 }, "useResidentialFallback": { "title": "Use residential proxy fallback", "type": "boolean", "description": "After 3 datacenter failures, retry via Apify residential proxy. Increases success rate to ~85-90% but adds ~$5/1K cost on failed profiles only. Recommended for stubborn profiles.", "default": false }, "concurrency": { "title": "Concurrent requests", "minimum": 1, "maximum": 20, "type": "integer", "description": "Parallel profile fetches. Higher = faster but more 429 risk. 5 is the validated sweet spot.", "default": 5 }, "maxItems": { "title": "Max profiles per run", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Hard cap on profiles processed in this run. Protects against runaway input.", "default": 500 }, "proxyConfiguration": { "title": "Proxy", "type": "object", "description": "Apify datacenter proxy (BUYPROXIES94952) is the validated optimum for cookie-free LinkedIn — 8x cheaper than residential at higher success rate. Override only if you have a specific reason.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "BUYPROXIES94952" ] } } } }, "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 } } } } } } } } } } ```