# Linkedin Profile Spider (`getdataforme/linkedin-profile-spider`) Actor LinkedIn Profile Spider extracts detailed LinkedIn profile data from profile URLs Collect names, headlines, work experience, company information, skills, locations, connections, and professional summaries. Ideal for recruitment, lead generation, market research, and talent intelligence. - **URL**: https://apify.com/getdataforme/linkedin-profile-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** Automation, Lead generation, Social media - **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $8.00 / 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 Spider ### Overview The LinkedIn Profile Spider is a powerful data extraction tool designed to collect publicly available LinkedIn profile information at scale. It supports both direct LinkedIn profile URLs and keyword-based profile searches, returning comprehensive professional profile data including employment history, skills, education, locations, and social metrics. This actor is ideal for recruitment, lead generation, market research, talent intelligence, competitor analysis, and professional networking insights. --- ### Features * Extract detailed LinkedIn profile information * Search profiles by LinkedIn URL or keyword * Collect current employment details * Retrieve complete work experience history * Extract skills, locations, and profile metadata * Capture professional summaries and headlines * Export data in JSON, CSV, Excel, XML, and other Apify-supported formats * Supports bulk profile processing --- ### Input #### Input Example You can provide either LinkedIn profile URLs or search keywords. ```json { "SearchQuery": [ "https://www.linkedin.com/in/rohan-salve-89159b204/" ] } ```` Or: ```json { "SearchQuery": [ "hari" ] } ``` #### Input Parameters | Parameter | Type | Required | Description | | ----------- | ----- | -------- | ------------------------------------------------- | | SearchQuery | Array | Yes | List of LinkedIn profile URLs or search keywords. | *** ### Output The actor returns detailed LinkedIn profile information. #### Top-Level Fields | Field | Description | | --------- | ----------------------------------- | | urls | Processed LinkedIn URLs | | public\_id | LinkedIn public profile identifier | | response | Complete profile information object | #### Profile Information | Field | Description | | ------------------------- | ------------------------------------------ | | id | LinkedIn profile ID | | full\_name | Full name | | first\_name | First name | | last\_name | Last name | | linkedin\_url | LinkedIn profile URL | | linkedin\_username | LinkedIn username/public identifier | | linkedin\_id | LinkedIn member ID | | headline | Professional headline | | summary | Profile summary/about section | | industry | Industry category | | job\_title | Current job title | | job\_company\_name | Current company | | job\_company\_linkedin\_url | Current company LinkedIn URL | | job\_company\_linkedin\_id | Current company LinkedIn ID | | job\_start\_date | Current role start date | | job\_summary | Current role description | | location\_name | Primary location | | location\_locality | City/locality | | location\_region | State/region | | location\_country | Country | | location\_continent | Continent | | linkedin\_connections | Number of LinkedIn connections | | inferred\_years\_experience | Estimated years of professional experience | #### Skills Returns an array of skills listed on the profile. Example: ```json "skills": [ "oral communication", "english", "analytical skills", "java", "artificial intelligence (ai)" ] ``` #### Locations Additional profile locations and geographic information. ```json "location_names": [], "regions": [], "countries": [] ``` #### Work Experience Returns complete professional experience history. ##### Experience Fields | Field | Description | | -------------------- | ------------------------------ | | company.name | Company name | | company.linkedin\_url | Company LinkedIn URL | | company.linkedin\_id | Company LinkedIn ID | | title.name | Job title | | start\_date | Employment start date | | end\_date | Employment end date | | location\_names | Associated locations | | summary | Job description | | is\_primary | Indicates current primary role | *** ### Sample Output ```json { "urls": [ "https://www.linkedin.com/in/rohan-salve-89159b204/" ], "public_id": "rohan-salve-89159b204", "response": { "id": "873358381", "full_name": "rohan salve", "headline": "senior executive", "industry": "information technology & services", "job_title": "senior executive", "job_company_name": "wipro", "location_country": "india", "linkedin_connections": 596, "inferred_years_experience": 6, "skills": [ "oral communication", "english", "analytical skills" ] } } ``` *** ### Use Cases #### Recruitment & Talent Sourcing Identify potential candidates and gather professional background information. #### Lead Generation Discover decision-makers, professionals, and business contacts. #### Market Research Analyze workforce trends, skills demand, and industry movement. #### Competitive Intelligence Monitor employee movements, organizational growth, and talent acquisition patterns. #### Sales Prospecting Build targeted outreach lists based on job titles, industries, locations, and experience. #### Professional Analytics Understand career trajectories, skill distributions, and employment trends. *** ### Getting Started 1. Open the actor in Apify Store. 2. Click **Try for free**. 3. Enter LinkedIn URLs or search keywords in the `SearchQuery` field. 4. Start the actor. 5. Wait for the run to complete. 6. Export the results in your preferred format. *** ### Output Formats The actor supports all standard Apify export formats: - JSON - CSV - Excel (XLSX) - XML - HTML - RSS *** ### Support Need custom output formats, additional fields, or assistance? **Email:** **Subject:** LinkedIn Profile Spider Support **Contact Form:** https://getdataforme.com/contact/ Our team is happy to help with custom requirements and troubleshooting. # Actor input Schema ## `SearchQuery` (type: `array`): The search query for the spider. ## `item_limit` (type: `integer`): Maximum items to scrape per actor run. Set to 0 for no limit. ## Actor input object example ```json { "SearchQuery": [ "https://www.linkedin.com/in/rohan-salve-89159b204/", "kiran" ], "item_limit": 10 } ``` # Actor output Schema ## `results` (type: `string`): Scraped data items from dataset # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/linkedin-profile-spider").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 = {} # Run the Actor and wait for it to finish run = client.actor("getdataforme/linkedin-profile-spider").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 '{}' | apify call getdataforme/linkedin-profile-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/linkedin-profile-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Linkedin Profile Spider", "description": "LinkedIn Profile Spider extracts detailed LinkedIn profile data from profile URLs Collect names, headlines, work experience, company information, skills, locations, connections, and professional summaries. Ideal for recruitment, lead generation, market research, and talent intelligence.", "version": "0.0", "x-build-id": "GmVndodLcd6ztsMWD" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~linkedin-profile-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-linkedin-profile-spider", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~linkedin-profile-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-linkedin-profile-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~linkedin-profile-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-linkedin-profile-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "SearchQuery": { "title": "Search Query", "type": "array", "description": "The search query for the spider.", "default": [ "https://www.linkedin.com/in/rohan-salve-89159b204/", "kiran" ], "items": { "type": "string" } }, "item_limit": { "title": "Item limit", "minimum": 0, "type": "integer", "description": "Maximum items to scrape per actor run. Set to 0 for no limit.", "default": 10 } } }, "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 } } } } } } } } } } ```