# LinkedIn Profile Scraper - No Login Required (`gopalakrishnan/linkedin-profile`) Actor Extract LinkedIn profile data - name, headline, about, location, current company, experience, education, and follower count - from a list of profile URLs. Works fully logged out, no cookies, zero risk to your own account. Pay only for profiles successfully scraped. - **URL**: https://apify.com/gopalakrishnan/linkedin-profile.md - **Developed by:** [Gopalakrishnan](https://apify.com/gopalakrishnan) (community) - **Categories:** Lead generation, Jobs, Automation - **Stats:** 5 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 profile scrapeds This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 (No Login / No Cookies / Safe) A production-grade, high-performance Apify Actor for scraping public LinkedIn profiles. Unlike other LinkedIn scrapers on the market, **this Actor does not require cookies, logins, or active account sessions**. It runs entirely logged-out, eliminating the risk of your personal or business LinkedIn accounts getting flagged or banned. --- ### 🚀 Key Differentiators & Benefits - **Zero Ban Risk**: No login credentials or cookies are required. Your LinkedIn accounts are 100% safe. - **No Cookie Expiry**: Since no session cookies are used, your scraping pipelines will never break due to "session expired" errors. - **Blazing Fast & Lightweight**: Built on top of Crawlee and CheerioCrawler (raw HTML parsing), avoiding heavy browser automation overhead. It is up to 10x faster and uses a fraction of the memory/CPU compared to Puppeteer/Playwright alternatives. - **Apify Proxy Integration**: Automatically routes requests through high-quality proxy IPs to ensure high success rates and prevent rate limiting. - **Pay-Per-Event (PPE) Friendly**: You only pay for what you successfully scrape! --- ### 🛠️ How it Works The Actor requests the public profile page (`https://www.linkedin.com/in/`) using a randomized desktop User-Agent and routes it through Apify Proxy. Public profiles contain structured schema.org `Person` markup embedded inside an `application/ld+json` script tag. The Actor parses this JSON-LD payload to extract rich, structured profile information without needing to authenticate or execute heavy client-side JavaScript. --- ### 📥 Input Settings The Actor accepts the following input fields: | Field | Type | Description | Required / Default | | -------------------- | ---------------- | -------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------ | | `profiles` | Array of strings | A list of LinkedIn usernames/slugs (e.g. `satyanadella`) or full profile URLs (e.g. `https://www.linkedin.com/in/satyanadella`). | **Required** | | `proxyConfiguration` | Object | Connection settings for proxy routing. Apify Proxy is used by default. | Default: `{ "useApifyProxy": true }` | | `maxProfiles` | Integer | Caps the maximum number of profiles to scrape. Useful for budget control. | Optional / Null | --- ### 📤 Output Fields The Actor produces clean, flat records in the default dataset. Below are the fields extracted: | Field | Type | Description | | ---------------- | ------- | --------------------------------------------------------------------------------- | | `fullName` | String | The full name of the user. | | `headline` | String | The profile's headline (often current job title/role). | | `about` | String | The user's biography/about summary. | | `location` | String | Geolocation (e.g. "Redmond, Washington, United States"). | | `currentCompany` | String | The company name of their current primary employment. | | `currentTitle` | String | Their current job title. | | `experience` | Array | Full employment history (company, company URL, title, location, start/end dates). | | `education` | Array | Education history (school name, school URL, start/end dates). | | `followers` | Integer | Total number of followers on their profile. | | `connections` | Integer | Total number of connections (if available). | | `skills` | Array | A list of endorsed/listed skills. | | `languages` | Array | Spoken/written languages. | | `profileUrl` | String | Canonical URL of the profile (`https://www.linkedin.com/in/`). | | `scrapeStatus` | String | Either `success` or `error`. | | `scrapedAt` | String | ISO timestamp of the scraping event. | #### Example Output JSON ```json { "fullName": "Satya Nadella", "headline": "Chairman and CEO at Microsoft", "about": "Satya Nadella is Chairman and CEO of Microsoft...", "location": "Redmond, Washington, United States", "currentCompany": "Microsoft", "currentTitle": "Chairman and CEO", "experience": [ { "company": "Microsoft", "companyUrl": "https://www.linkedin.com/company/microsoft", "location": "Greater Seattle Area", "title": "Chairman and CEO", "startDate": "2014-02", "endDate": null } ], "education": [ { "school": "University of Chicago Booth School of Business", "schoolUrl": "https://www.linkedin.com/school/chicago-booth/", "startDate": "1995", "endDate": "1997" } ], "followers": 10500000, "connections": 500, "skills": ["Enterprise Software", "Cloud Computing", "SaaS"], "languages": ["English", "Hindi"], "profileUrl": "https://www.linkedin.com/in/satyanadella", "scrapeStatus": "success", "scrapedAt": "2026-06-21T18:45:00.000Z" } ```` *** ### 💰 Pay-Per-Event (PPE) Pricing This Actor is configured with Pay-Per-Event billing: 1. **`actor-start`**: Charged once per Actor run to cover initialization costs. 2. **`profile-scraped`**: Charged per successfully scraped profile. Profiles that fail to scrape (e.g. login-walled, invalid username) are marked with `scrapeStatus: 'error'` and are **not** charged the profile success fee. *** ### 🔗 Sibling Actors If you are scraping LinkedIn data for lead generation or market analysis, you may also find our other specialized tools helpful: - **[LinkedIn Jobs Scraper](https://apify.com/gopalakrishnan/linkedin-jobs)**: Extract job listings, descriptions, salary details, and employer info without any session cookies. # Actor input Schema ## `profiles` (type: `array`): LinkedIn profile URLs or usernames/slugs to scrape (e.g. 'satyanadella' or 'https://www.linkedin.com/in/satyanadella') ## `proxyConfiguration` (type: `object`): Apify Proxy settings (required). Only datacenter/residential proxies should be used. ## `maxProfiles` (type: `integer`): Maximum number of profiles to scrape. Leave empty for no limit. ## Actor input object example ```json { "profiles": [ "satyanadella" ], "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `profiles` (type: `string`): No description # 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 = { "profiles": [ "satyanadella" ] }; // Run the Actor and wait for it to finish const run = await client.actor("gopalakrishnan/linkedin-profile").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 = { "profiles": ["satyanadella"] } # Run the Actor and wait for it to finish run = client.actor("gopalakrishnan/linkedin-profile").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 '{ "profiles": [ "satyanadella" ] }' | apify call gopalakrishnan/linkedin-profile --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=gopalakrishnan/linkedin-profile", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Profile Scraper - No Login Required", "description": "Extract LinkedIn profile data - name, headline, about, location, current company, experience, education, and follower count - from a list of profile URLs. Works fully logged out, no cookies, zero risk to your own account. Pay only for profiles successfully scraped.", "version": "1.0", "x-build-id": "7E8tAqTBvFwhsGHlM" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/gopalakrishnan~linkedin-profile/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-gopalakrishnan-linkedin-profile", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/gopalakrishnan~linkedin-profile/runs": { "post": { "operationId": "runs-sync-gopalakrishnan-linkedin-profile", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/gopalakrishnan~linkedin-profile/run-sync": { "post": { "operationId": "run-sync-gopalakrishnan-linkedin-profile", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "profiles" ], "properties": { "profiles": { "title": "Profiles", "type": "array", "description": "LinkedIn profile URLs or usernames/slugs to scrape (e.g. 'satyanadella' or 'https://www.linkedin.com/in/satyanadella')", "items": { "type": "string" } }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Apify Proxy settings (required). Only datacenter/residential proxies should be used.", "default": { "useApifyProxy": true } }, "maxProfiles": { "title": "Max Profiles", "minimum": 1, "type": "integer", "description": "Maximum number of profiles to scrape. Leave empty for no limit." } } }, "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 } } } } } } } } } } ```