# Linkedin Profile Finder (`scrapedrift/linkedin-profile-finder`) Actor LinkedIn Profile Finder helps locate and extract publicly available LinkedIn profile data, including names, job titles, companies, locations, and profile URLs. Ideal for B2B lead generation, recruiting, sales outreach, and building accurate professional contact lists quickly and efficiently. - **URL**: https://apify.com/scrapedrift/linkedin-profile-finder.md - **Developed by:** [ScrapeDrift](https://apify.com/scrapedrift) (community) - **Categories:** Lead generation, Jobs, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 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 Profile Finder 🚀 Searching for the right profiles one by one is slow and tedious—especially when you need leads for outreach or research. **LinkedIn Profile Finder** helps you discover LinkedIn profiles in bulk using your keywords (no login required). It’s a practical LinkedIn search tool for people doing LinkedIn people search, lead generation, or finding LinkedIn URL leads fast. This is built for marketers, data analysts, and researchers who want structured profile links without manual browsing. In one run, you can collect up to hundreds of profile records quickly (with higher limits on paid plans) and keep everything neatly organized in an Apify dataset. --- ### See the Data: Sample Output Here's a real record from a single run: ```json { "keyword": "marketing manager", "url": "https://www.linkedin.com/in/jane-doe-123456789/", "description_snippet": "Experienced marketing manager focused on B2B demand generation and brand strategy.", "source": "Search Engine", "status": "success", "error_message": null } ```` | Field | Type | What It Tells You | |---|---|---| | `keyword` | string | Which keyword produced this profile link—useful for grouping and reporting by intent. | | `url` | string | The LinkedIn profile URL so you can open the lead instantly or feed it into downstream enrichment. | | `description_snippet` | string | A short snippet from the source page to help you judge relevance before outreach. | | `source` | string | Indicates where the record came from (for this actor, it’s labeled as “Search Engine”). | | `status` | string | Whether the run treated the output as successfully collected (useful for automation pipelines). | | `error_message` | string | Present only when something goes wrong; otherwise `null` to keep datasets clean. | | `username` | string | If you later enrich content, the profile username can be extracted from the profile URL format. | | `emails` | array | If you later enrich descriptions, this is where detected email addresses end up (when available). | | `userLink` | string | A normalized profile link used during enrichment so downstream steps have a consistent URL. | | `source_description` | string | A raw description input used during enrichment (when enrichment is enabled in a workflow). | Export your full dataset as JSON, CSV, or Excel from the Apify dashboard. *** ### Setting It Up Drop this into your `input.json` and you're ready to go: ```json { "keywords": ["software engineer", "marketing manager"], "country": "United States" } ``` | Parameter | Required | What It Does | |---|---|---| | `keywords` | ✅ | A list of keywords the actor uses to discover LinkedIn profile candidates. | | `country` | ⬜ | Filters results to a target country (for example, “United States”). | *** ### What It Does LinkedIn Profile Finder automatically discovers LinkedIn profiles based on the keywords you provide and writes the results into your Apify dataset. #### Finds relevant LinkedIn profiles by keyword You provide job- and role-like keywords, and the actor collects matching LinkedIn profile URLs along with a short `description_snippet` to help you validate relevance quickly. This makes LinkedIn profile finder workflows much faster than manual searching. #### Uses your country filter for targeted lead discovery When you set `country`, the actor focuses the results toward that target market. This helps when you’re running LinkedIn contact finder campaigns that need geographic alignment. #### Produces clean, dataset-ready records Each result is pushed with consistent fields: `keyword`, `url`, `description_snippet`, and `source`. The dataset view is set up to display these as a table with a clickable “View Profile” link. #### Built for resilience with retries and fallbacks The actor includes retry logic and resilience patterns so temporary issues don’t immediately end your run. For free-tier users, the run is capped to help keep workloads predictable. #### Keeps results controlled per run LinkedIn Profile Finder enforces limits per run depending on whether you’re on a paid plan or free tier. This helps prevent runaway runs while still supporting bulk discovery on demand. Overall, LinkedIn Profile Finder streamlines LinkedIn people search so you can turn keyword ideas into a usable list of LinkedIn URLs fast. *** ### Why LinkedIn Profile Finder? There are plenty of ways to pull data from public web sources—here’s why LinkedIn Profile Finder stands out. #### Simple inputs, useful outputs You only need `keywords` (plus an optional `country`) and you immediately get profile URLs with a matching `description_snippet`. That structure is ideal for downstream lead generation LinkedIn finder pipelines. #### Designed to work without an account on LinkedIn You don’t provide any LinkedIn login or session details. This keeps the setup lightweight for LinkedIn profile lookup and research workflows. #### Works well for bulk prospecting and reporting Because results are written to the dataset as items are collected, you can review progress and export quickly when you hit your target volume—making it a practical LinkedIn URL finder for teams running repeated searches. *** ### Real-World Use Cases Here’s how different teams put LinkedIn Profile Finder to work: **Sales Teams**\ A sales lead generation manager needs a steady stream of LinkedIn leads for outreach. They run the actor with role keywords (like marketing manager) and a target country, then import the dataset into their CRM workflow—skipping the manual “tab opening” part entirely. **Marketing Agencies**\ An agency building a campaign shortlist wants LinkedIn profile finder outputs tied to specific keywords. They run multiple keywords in one go, use `description_snippet` to quickly assess relevance, and then hand a clean list of profile URLs to their outreach team. **Freelance Researchers**\ A researcher preparing a competitive landscape report needs LinkedIn profile search results organized by intent. They export the dataset and join it with other datasets by `keyword` and profile `url`—so each segment is traceable. **Automation & Data Engineers**\ A developer wants to automate parts of LinkedIn contact finder workflows. They trigger the run, consume the dataset via Apify’s API, and push the `url` list into their enrichment and deduplication pipeline. **Prospecting for Specific Regions**\ A team running targeted employee LinkedIn finder research focuses on one geography at a time. By using the `country` input, they keep results closer to their target market for better list quality. *** ### How to Run It No code required. Here's how to get your first results in under 5 minutes: 1. **Open the actor on Apify**\ Go to the actor page in the Apify console: https://console.apify.com. 2. **Enter your inputs**\ Add your role terms in `keywords` and optionally set `country` to narrow the results. 3. **Configure proxy settings briefly (if you use them)**\ If you want extra reliability for larger runs, enable proxy support in your run settings. 4. **Start the run and watch the live log**\ Use the live logs to confirm the actor is processing your keywords and collecting records. 5. **Open the Dataset tab to see live results**\ Your dataset will include `keyword`, `url`, `description_snippet`, and `source` in a table view. 6. **Export in your preferred format**\ Download JSON, CSV, or Excel from the Apify dashboard when the run completes. The whole setup takes under 5 minutes — results start appearing within seconds of launch. *** ### Export & Integration Options Once your data is collected, LinkedIn Profile Finder fits directly into your existing workflow. You can export your dataset from the Apify dashboard as JSON, CSV, or Excel. This makes it easy to move from LinkedIn people search discovery into spreadsheets, CRM imports, or analyst notebooks. For automation and scale, you can integrate via Apify’s API, connect tools using Zapier/Make, and trigger downstream actions with webhooks when runs complete. You can also schedule runs to refresh lists automatically on a recurring basis. *** ### Pricing LinkedIn Profile Finder runs on Apify, which includes a **free tier** — no credit card needed to start. Free runs have a capped maximum number of profiles per run, while paid plans allow much larger workloads. If you need heavier usage, Apify’s subscription plans and pay-as-you-go compute model help you scale without changing your workflow. Start free at — scale up when you need. *** ### Reliability & Limitations | What We Handle | How | |---|---| | Rate/traffic issues | Includes retries and resilience patterns so runs keep going when possible | | Reliability for repeated scraping | Supports proxy usage for more stable collection | | Run size control | Free tier vs paid plan differences cap the maximum number of profiles per run | | Clean dataset output | Results are pushed with consistent fields (`keyword`, `url`, `description_snippet`, `source`) | | Basic error handling | If problems occur, you can detect failures via dataset records and the actor logs | Limitations: the actor is intended for publicly available profile discovery. It does not access login-gated or private content, and profile relevance depends on what’s publicly displayed in the source description snippets. For enterprise-scale needs or custom configurations, reach out and we'll help. *** ### Frequently Asked Questions #### Is there a free plan? Yes, LinkedIn Profile Finder is available with an Apify free tier. Free runs are capped to a maximum number of profiles per run to keep usage predictable. #### Do I need to log in or create an account on LinkedIn? No. LinkedIn Profile Finder is designed to work without requiring you to log in to LinkedIn. #### How accurate is the extracted data? The actor collects profile URLs and associated `description_snippet` text that appears in publicly available sources. Accuracy depends on what’s visible for each profile and how clearly it matches your `keywords`. #### How many results can I get per run? Your results are capped per run depending on whether you’re on a free tier or a paid plan. On free tier, the actor limits output to a maximum number of profiles per run. #### How fresh is the data? Data freshness depends on when publicly available pages are updated and when you run the actor. The actor runs on-demand, so you can refresh your dataset whenever you need updated leads. #### Is this legal? Does it comply with GDPR / CCPA? LinkedIn Profile Finder uses publicly available data and does not require login to access information. Still, it’s your responsibility to comply with GDPR, CCPA, platform Terms of Service, and any local regulations when collecting and storing personal data. #### Can I export to Google Sheets or Excel? Yes. You can export from the Apify dataset tab as JSON, CSV, or Excel, and then import into Google Sheets or Excel. You can also use integrations via Zapier/Make for easier automation. #### Can I schedule this to run automatically? Yes. You can schedule actor runs on Apify for recurring updates and automated LinkedIn profile tracker workflows. #### Can I access results via the API? Yes. Since results are stored in an Apify dataset, you can access them programmatically via the Apify API as part of a larger automation pipeline. #### What happens when the actor encounters an error? The actor uses retries and resilience patterns, and it logs progress so you can monitor what happened. If something fails, you’ll typically see fewer collected records for that keyword, and the actor logs will help you diagnose issues. *** ### Get Help & Use Responsibly Got a question about LinkedIn Profile Finder or a feature you'd like added? Reach out at . We welcome feedback and ideas that improve how your LinkedIn profile finder or LinkedIn lead finder workflow delivers value. **LinkedIn Profile Finder collects data only from publicly available data.** It does not access private accounts, login-gated pages, or password-protected content. Use responsibly, ethically, and only for lawful purposes. If you need data removal, contact . Use responsibly, ethically, and only for lawful purposes. # Actor input Schema ## `keywords` (type: `array`): List of keywords to search for LinkedIn profiles (e.g., 'software engineer', 'marketing manager'). ## `country` (type: `string`): Select the target country for leads. ## Actor input object example ```json { "keywords": [ "software engineer", "marketing manager" ], "country": "United States" } ``` # 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": [ "software engineer", "marketing manager" ], "country": "United States" }; // Run the Actor and wait for it to finish const run = await client.actor("scrapedrift/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 = { "keywords": [ "software engineer", "marketing manager", ], "country": "United States", } # Run the Actor and wait for it to finish run = client.actor("scrapedrift/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 '{ "keywords": [ "software engineer", "marketing manager" ], "country": "United States" }' | apify call scrapedrift/linkedin-profile-finder --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapedrift/linkedin-profile-finder", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Linkedin Profile Finder", "description": "LinkedIn Profile Finder helps locate and extract publicly available LinkedIn profile data, including names, job titles, companies, locations, and profile URLs. Ideal for B2B lead generation, recruiting, sales outreach, and building accurate professional contact lists quickly and efficiently.", "version": "1.0", "x-build-id": "3q2Yr31R6dUp2tx3l" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapedrift~linkedin-profile-finder/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapedrift-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapedrift~linkedin-profile-finder/runs": { "post": { "operationId": "runs-sync-scrapedrift-linkedin-profile-finder", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapedrift~linkedin-profile-finder/run-sync": { "post": { "operationId": "run-sync-scrapedrift-linkedin-profile-finder", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "keywords" ], "properties": { "keywords": { "title": "Search Keywords", "minItems": 1, "uniqueItems": true, "type": "array", "description": "List of keywords to search for LinkedIn profiles (e.g., 'software engineer', 'marketing manager').", "items": { "type": "string" } }, "country": { "title": "Target Country", "enum": [ "United States", "United Kingdom", "Canada", "Australia", "India", "Germany", "France", "Spain", "Italy", "Brazil", "Mexico", "Japan", "South Korea", "China", "Singapore", "United Arab Emirates", "Netherlands", "Sweden", "Norway", "Denmark", "Switzerland", "Belgium", "Austria", "Ireland", "New Zealand", "South Africa" ], "type": "string", "description": "Select the target country for leads.", "default": "United States" } } }, "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 } } } } } } } } } } ```