# LinkedIn Profile Finder & Discovery (`maged120/linkedin-profile-finder`) Actor Finds and discovers public LinkedIn profile matches by name, role, profession, and company. - **URL**: https://apify.com/maged120/linkedin-profile-finder.md - **Developed by:** [Maged](https://apify.com/maged120) (community) - **Categories:** Lead generation, Automation, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 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. 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/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 Profile Finder** is a **LinkedIn scraper** that helps you **find and scrape public LinkedIn profiles** by name, job title, company, profession, language, or region. Use it to build candidate lists, find B2B leads, research companies, source talent, and export clean profile discovery data — **free to start, no login or cookies required**. ### What does LinkedIn Profile Finder do? LinkedIn Profile Finder searches and scrapes public profile candidates on [LinkedIn](https://www.linkedin.com/) that match your criteria. Enter a job title such as "Software Engineer", a company such as "IBM", a person's name, a profession, language, or region, then choose how many profile results you want. The Actor returns structured profile discovery data, including public profile URL, profile title, role/company context, visible profile description, match criteria, and collection timestamp. Results are saved to a dataset and can be downloaded as JSON, CSV, Excel, or HTML, or accessed through the API, schedules, webhooks, and integrations. ### Why use LinkedIn Profile Finder? - Find LinkedIn profiles by **job title and company**. - Build recruiting and talent sourcing lists for specific roles. - Discover B2B leads and decision-maker candidates by profession or organization. - Research employees, founders, engineers, salespeople, marketers, recruiters, or executives. - Export clean profile URLs and snippets instead of copying profile data manually. - Run repeatable LinkedIn profile discovery workflows. ### How to find LinkedIn profiles by company, title, or name 1. Open the Actor and go to the **Input** tab. 2. Enter at least one search criterion: `name`, `position`, `company`, or `profession`. 3. Optionally choose `language` and `region` to focus results. 4. Set `limit` to control the maximum number of matching profiles. 5. Start the Actor and download or integrate the dataset when the run finishes. For best results, combine `position` and `company`, for example "Product Manager" and "Microsoft", or add a `name` when checking a specific person. ### Input | Field | Description | | --- | --- | | `name` | Optional person's name to match, useful for specific profile lookup. | | `position` | Optional job title, role, or seniority, such as Software Engineer, Founder, Recruiter, or Sales Manager. | | `company` | Optional company, employer, startup, agency, university, or organization name. | | `profession` | Optional broader profession, industry, skill, or specialty such as machine learning, cybersecurity, finance, or marketing. | | `language` | Optional language to prioritize for localized profile discovery. | | `region` | Optional region to prioritize for country-focused profile discovery. | | `limit` | Maximum number of matching profile rows to save. | Example input: ```json { "position": "Software Engineer", "company": "IBM", "language": "english", "region": "united_states", "limit": 25 } ```` ### Output Each dataset item is one public LinkedIn profile candidate. You can download the dataset in various formats such as JSON, HTML, CSV, or Excel. ```json { "profileUrl": "https://www.linkedin.com/in/example-profile/", "title": "Example Person - Software Engineer - Example Company", "subtext": "Software Engineer - Example Company", "description": "Public profile summary and visible profile context.", "extraInfo": { "matchedPosition": "Software Engineer", "matchedCompany": "Example Company", "matchedLanguage": "english", "matchedRegion": "united_states" }, "collectedAt": "2026-07-03T12:00:00+00:00" } ``` ### Data table | Field | Type | Description | | --- | --- | --- | | `profileUrl` | Link | Canonical public LinkedIn profile URL. | | `title` | Text | Main visible profile title or profile headline. | | `subtext` | Text | Role, company, or headline context when available. | | `description` | Text | Public profile snippet and visible profile context. | | `extraInfo` | Object | Search criteria that contributed to the match. | | `collectedAt` | Date | Timestamp when the profile row was collected. | ### How much does it cost to find LinkedIn profiles? Cost depends mainly on the number of profile results you save and how often you run the Actor. Start with a small `limit` such as 10-25 profiles, review match quality, then increase the limit for larger recruiting, prospecting, or market research workflows. ### Tips for better LinkedIn profile search results - Use both `position` and `company` for precise company employee discovery. - Add `name` when you want to find a specific public profile. - Use `profession` for broad prospecting, such as "machine learning", "real estate", "sales operations", or "cybersecurity". - Use `region` when you need profiles focused on a specific country or market. - Keep `limit` small while testing a new search, then scale once results look relevant. ### FAQ, disclaimers, and support Is this legal? This Actor is intended for discovering publicly available profile information. You are responsible for using the output in compliance with applicable laws, LinkedIn terms, privacy rules, and your own internal policies. Why did I get fewer results than my limit? Public profile availability and match quality vary by role, company, name, profession, language, and region. Broaden the criteria if you need more candidates. Can I use this for recruiting or sales prospecting? Yes, it is designed for public profile discovery workflows such as candidate sourcing, lead research, account mapping, and company research. You are responsible for compliant outreach and data handling. Can I request changes? Use the Actor's Issues tab for bug reports, feature requests, or custom solution inquiries. **Need something custom?** If you need a tailored version — different data fields, a specific target site, bulk enrichment, CRM integration, or a fully custom scraping workflow — feel free to reach out directly. Contact the developer through the Actor's Issues tab or via email at **mkingm123@gmail.com**. Custom work is welcome. # Actor input Schema ## `name` (type: `string`): Optional person's name to match. ## `position` (type: `string`): Optional job title, role, or position. ## `company` (type: `string`): Optional company or organization name. ## `profession` (type: `string`): Optional broader profession, industry, or specialty. ## `language` (type: `string`): Optional language to prioritize when finding matching profiles. ## `region` (type: `string`): Optional region to prioritize when finding matching profiles. ## `limit` (type: `integer`): Maximum number of matching profile rows to save. ## Actor input object example ```json { "position": "Software Engineer", "company": "IBM", "limit": 25 } ``` # Actor output Schema ## `dataset` (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 = { "position": "Software Engineer", "company": "IBM", "limit": 25 }; // Run the Actor and wait for it to finish const run = await client.actor("maged120/linkedin-profile-finder").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 = { "position": "Software Engineer", "company": "IBM", "limit": 25, } # Run the Actor and wait for it to finish run = client.actor("maged120/linkedin-profile-finder").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 '{ "position": "Software Engineer", "company": "IBM", "limit": 25 }' | apify call maged120/linkedin-profile-finder --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=maged120/linkedin-profile-finder", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Profile Finder & Discovery", "description": "Finds and discovers public LinkedIn profile matches by name, role, profession, and company.", "version": "0.1", "x-build-id": "6OtEdC7ZxFF77MQzU" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/maged120~linkedin-profile-finder/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-maged120-linkedin-profile-finder", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/maged120~linkedin-profile-finder/runs": { "post": { "operationId": "runs-sync-maged120-linkedin-profile-finder", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/maged120~linkedin-profile-finder/run-sync": { "post": { "operationId": "run-sync-maged120-linkedin-profile-finder", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "name": { "title": "Name", "type": "string", "description": "Optional person's name to match." }, "position": { "title": "Position or Title", "type": "string", "description": "Optional job title, role, or position." }, "company": { "title": "Company", "type": "string", "description": "Optional company or organization name." }, "profession": { "title": "Profession or Specialty", "type": "string", "description": "Optional broader profession, industry, or specialty." }, "language": { "title": "Language", "enum": [ "arabic", "chinese_simplified", "chinese_traditional", "czech", "danish", "dutch", "english", "estonian", "finnish", "french", "german", "greek", "hebrew", "hindi", "hungarian", "icelandic", "indonesian", "italian", "japanese", "korean", "latvian", "lithuanian", "norwegian", "persian", "polish", "portuguese", "romanian", "russian", "spanish", "swedish", "thai", "turkish", "ukrainian", "vietnamese" ], "type": "string", "description": "Optional language to prioritize when finding matching profiles." }, "region": { "title": "Region", "enum": [ "afghanistan", "albania", "algeria", "andorra", "argentina", "australia", "austria", "belgium", "brazil", "canada", "chile", "china", "colombia", "czech_republic", "denmark", "egypt", "finland", "france", "germany", "greece", "hong_kong", "india", "indonesia", "ireland", "israel", "italy", "japan", "kenya", "malaysia", "mexico", "netherlands", "new_zealand", "nigeria", "norway", "pakistan", "philippines", "poland", "portugal", "romania", "russia", "saudi_arabia", "singapore", "south_africa", "south_korea", "spain", "sweden", "switzerland", "taiwan", "thailand", "turkey", "ukraine", "united_kingdom", "united_states", "vietnam" ], "type": "string", "description": "Optional region to prioritize when finding matching profiles." }, "limit": { "title": "Maximum Profiles", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of matching profile rows to save.", "default": 25 } } }, "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 } } } } } } } } } } ```