# Linkedin Profile Lead Scraper (`scrapapi/linkedin-profile-lead-scraper`) Actor - **URL**: https://apify.com/scrapapi/linkedin-profile-lead-scraper.md - **Developed by:** [ScrapAPI](https://apify.com/scrapapi) (community) - **Categories:** Lead generation, Social media, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.99 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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** Lead Scraper πŸ“± Discover the comprehensive **data** you can **extract** from **LinkedIn** profiles using our advanced lead scraper. ### Support and feedback - **Bug reports**: Open a ticket in the repository Issues section - **Custom features**: Contact our enterprise support team *Lead: scrapier.io@gmail.com * ### Extractable Data Table πŸ“Š | Data Type | Description | | --- | --- | ### Key Features of **LinkedIn** Lead Scraper Here are the **standout features** that make the **LinkedIn** Lead Scraper a **top-tier tool** for **marketers**, **agencies**, and **researchers**: ### How to use **LinkedIn** Lead Scraper πŸš€ Follow this **simple, step-by-step guide** to start extracting **LinkedIn** leads today: ### Use Cases 🎯 ### **LinkedIn** Lead Scraper Legal Guidelines βš–οΈ **Yes**β€”scraping **LinkedIn** is **legal** as long as you follow **ethical** and **compliant** practices. The **LinkedIn** Lead Scraper extracts only **publicly available** information from **public** **LinkedIn** profiles, making it **safe** and **compliant** for **research**, **marketing**, and **analysis**. #### Legal & Ethical Guidelines ### Input Parameters 🧩 πŸ“¦ Example Input (JSON) ```json { "keywords": ["Linkedin Profile Lead Scraper"], "country": "Global", "maxLeadNumbers": 20, "platform": "LinkedIn", "engine": "legacy" } ```` ### Input Table | Data Type | Description | | --- | --- | | keywords | Keywords to find relevant profiles | | country | Country setting (Global) | | maxLeadNumbers | Maximum leads to collect (default 20) | | platform | Platform to scrape (LinkedIn) | | engine | Engine type (legacy) | | proxyConfiguration | Optional proxy settings | ### Output Format πŸ“€ πŸ“ Example Output (JSON) ```json [ { "network": "LinkedIn", "keyword": "Linkedin Profile Lead Scraper", "title": "Google's Single-Benefit Marketing Strategy for Chrome ...", "description": "βœ“For years, once we created a Gmail account, we couldn't change the username (the part before @ gmail.com ). ... Grand Rapids Marketing Co. Read more", "url": "https://www.linkedin.com/posts/phill-agnew_heres-how-google-marketed-chrome-browser-activity-7404878510214914048-dLxI", "lead": "before@gmail.com" } ] ``` ### Output Table | Data Type | Description | | --- | --- | | network | Identifies LinkedIn as the source | | keyword | Keyword that triggered the result (Linkedin Profile Lead Scraper) | | title | Profile title or username | | description | Public bio snippet with contact info | | url | Direct LinkedIn profile link | | lead | Extracted lead address | ### FAQ ❓ # Actor input Schema ## `keywords` (type: `array`): List of keywords to search for on Linkedin (e.g., \['marketing', 'founder', 'business']). The actor will search Google for Linkedin profiles/posts containing these keywords and extract email addresses. ## `platform` (type: `string`): Select platform. ## `location` (type: `string`): Optional: Add location to search query (e.g., 'London', 'New York'). Leave empty to search globally. ## `emailDomains` (type: `array`): Optional: Filter results to only include emails from specific domains (e.g., \['@gmail.com', '@outlook.com']). Leave empty to collect all email domains. ## `maxEmails` (type: `integer`): Maximum number of emails to collect per keyword (default: 20). ## `engine` (type: `string`): Choose scraping engine. πŸš€ Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. πŸ”§ Legacy: Uses GOOGLE\_SERP proxy with traditional selectors - more reliable but slower and more expensive. ## `proxyConfiguration` (type: `object`): Choose which proxies to use. By default, no proxy is used. If Google rejects or blocks the request, the actor will automatically fallback to datacenter proxy, then residential proxy with 3 retries. ## Actor input object example ```json { "keywords": [ "marketing" ], "platform": "Linkedin", "location": "", "emailDomains": [ "@gmail.com" ], "maxEmails": 20, "engine": "legacy", "proxyConfiguration": { "useApifyProxy": false } } ``` # 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 = { "keywords": [ "marketing" ], "emailDomains": [ "@gmail.com" ], "proxyConfiguration": { "useApifyProxy": false } }; // Run the Actor and wait for it to finish const run = await client.actor("scrapapi/linkedin-profile-lead-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "keywords": ["marketing"], "emailDomains": ["@gmail.com"], "proxyConfiguration": { "useApifyProxy": False }, } # Run the Actor and wait for it to finish run = client.actor("scrapapi/linkedin-profile-lead-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": [ "marketing" ], "emailDomains": [ "@gmail.com" ], "proxyConfiguration": { "useApifyProxy": false } }' | apify call scrapapi/linkedin-profile-lead-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapapi/linkedin-profile-lead-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Linkedin Profile Lead Scraper", "version": "0.1", "x-build-id": "NmEVYIYaQV16EO7g6" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapapi~linkedin-profile-lead-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapapi-linkedin-profile-lead-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/scrapapi~linkedin-profile-lead-scraper/runs": { "post": { "operationId": "runs-sync-scrapapi-linkedin-profile-lead-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/scrapapi~linkedin-profile-lead-scraper/run-sync": { "post": { "operationId": "run-sync-scrapapi-linkedin-profile-lead-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": [ "keywords" ], "properties": { "keywords": { "title": "Keywords", "type": "array", "description": "List of keywords to search for on Linkedin (e.g., ['marketing', 'founder', 'business']). The actor will search Google for Linkedin profiles/posts containing these keywords and extract email addresses.", "items": { "type": "string" } }, "platform": { "title": "Platform", "enum": [ "Linkedin" ], "type": "string", "description": "Select platform.", "default": "Linkedin" }, "location": { "title": "Location Filter", "type": "string", "description": "Optional: Add location to search query (e.g., 'London', 'New York'). Leave empty to search globally.", "default": "" }, "emailDomains": { "title": "Email Domains Filter", "type": "array", "description": "Optional: Filter results to only include emails from specific domains (e.g., ['@gmail.com', '@outlook.com']). Leave empty to collect all email domains.", "items": { "type": "string" } }, "maxEmails": { "title": "Maximum Emails per Keyword", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum number of emails to collect per keyword (default: 20).", "default": 20 }, "engine": { "title": "Engine", "enum": [ "legacy" ], "type": "string", "description": "Choose scraping engine. πŸš€ Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. πŸ”§ Legacy: Uses GOOGLE_SERP proxy with traditional selectors - more reliable but slower and more expensive.", "default": "legacy" }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Choose which proxies to use. By default, no proxy is used. If Google rejects or blocks the request, the actor will automatically fallback to datacenter proxy, then residential proxy with 3 retries." } } }, "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 } } } } } } } } } } ```