# LinkedIn Recruiter Pro (`fixitfoundry/linkedin-recruiter-pro`) Actor Advanced LinkedIn profile finder with email verification, AI fit scoring, and multiple search modes. Find candidates via Google dorking, direct search, or company employee lookup. - **URL**: https://apify.com/fixitfoundry/linkedin-recruiter-pro.md - **Developed by:** [Jesse Casco](https://apify.com/fixitfoundry) (community) - **Categories:** Social media, Automation, Lead generation - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 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 Recruiter Pro V2 **Version:** 1.0 — Apify Actor for finding LinkedIn candidate profiles via public search. **Price:** $0.05/profile (Pay Per Event — PPE) --- ### Overview LinkedIn Recruiter Pro finds publicly available LinkedIn profiles using Google search and LinkedIn's public directory endpoints, enriches them with estimated email addresses (with optional external verification), and scores candidates against a job description using algorithmic keyword matching ("AI fit scoring"). > **⚠️ IMPORTANT — WHAT THIS ACTOR DOES AND DOES NOT DO** > - This tool **only** accesses publicly available data via search engines and public LinkedIn directory endpoints. > - **No login, authentication bypass, or API abuse** is performed. > - Profile data (work history, education, skills) is **extracted from search result snippets only** — not from individual LinkedIn profile pages. This means `workHistory`, `education`, and detailed `skills` arrays will be **empty** unless the user provides a skills filter in the input. > - Email addresses are **ESTIMATED** using common corporate patterns and are **NOT verified** unless `verifyEmail: true` is set with a valid `emailVerificationApiKey`. > - The "AI fit score" is an **algorithmic keyword overlap estimate**, not human judgment. It should not be used as the sole basis for hiring decisions. > - Users must comply with applicable laws, LinkedIn's Terms of Service, and data protection regulations (GDPR, CCPA, etc.). > - **Intended for legitimate recruiting purposes only.** --- ### Features | Feature | Description | |---------|-------------| | **Multiple Search Modes** | Google dorking (default), direct LinkedIn public search, company employee lookup | | **Apify Proxy Integration** | Automatic proxy rotation to reduce CAPTCHA blocking | | **CAPTCHA Detection** | Detects Google CAPTCHA challenges and logs clear warnings | | **Error Boundaries** | Per-query and per-profile error handling — one failure doesn't crash the whole run | | **URL Deduplication** | Same profile across multiple queries is only saved once | | **Email Enrichment** | Pattern-based email estimation with confidence scoring | | **Email Verification** | Optional external API verification (flags: verified / unverified / estimated) | | **AI Fit Scoring** | TF-IDF style keyword overlap scoring against a job description (0-100) | | **Bulk Export** | CSV, JSON, and JSONL output formats | | **Rate Limiting** | Configurable delay, User-Agent rotation | | **Profile Data** | Name, headline, location, company (from search input/snippet) | --- ### Input Parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `searchQueries` | `string[]` | **required** | List of search strings (e.g., `["Senior Software Engineer"]`) | | `jobTitle` | `string` | — | Filter by job title | | `location` | `string` | — | Filter by location | | `company` | `string` | — | Filter by company | | `skills` | `string` | — | Comma-separated skills filter | | `jobDescription` | `string` | — | Job description text for fit scoring | | `maxResults` | `number` | `25` | Max profiles (1–1000) | | `enrichEmail` | `boolean` | `true` | Estimate email addresses | | `verifyEmail` | `boolean` | `false` | Verify emails via AbstractAPI or Disify | | `emailVerificationApiKey` | `string` | — | Your AbstractAPI key for email verification (optional, without it falls back to Disify free API) | | `searchMode` | `string` | `googleDork` | `googleDork`, `directSearch`, or `companyEmployees` | | `delayBetweenRequests` | `number` | `2` | Seconds between HTTP requests | | `outputFormat` | `string` | `json` | `json`, `csv`, or `jsonl` | --- ### Search Modes #### `googleDork` (default) Uses Google search with `site:linkedin.com/in/` queries to find public LinkedIn profiles. Works without any LinkedIn access. Uses Apify proxy for improved reliability. #### `directSearch` Searches LinkedIn's public directory endpoints (`linkedin.com/pub/dir/`). Limited but useful for well-known names. #### `companyEmployees` Uses Google dorking to find employees of a specific company: `site:linkedin.com/in/ "at {CompanyName}"` --- ### Output Fields Each profile record contains: | Field | Type | Description | |-------|------|-------------| | `name` | `string` | Full name extracted from profile URL | | `firstName` | `string` | First name | | `lastName` | `string` | Last name | | `headline` | `string` | Profile headline / search query | | `location` | `string` | Location from search filter | | `currentCompany` | `string` | Current employer (from search filter or snippet) | | `currentTitle` | `string` | Current job title | | `website` | `string` | LinkedIn profile URL | | `url` | `string` | LinkedIn profile URL | | `estimatedEmail` | `string` | Best-estimated email address | | `emailConfidence` | `string` | `high`, `medium`, `low`, or `null` | | `emailStatus` | `string` | `verified`, `unverified`, `estimated`, or `none` | | `fitScore` | `number` | Algorithmic fit score (0–100) against job description | | `searchQuery` | `string` | The search query that found this profile | | `extractedAt` | `string` | ISO timestamp when processed | > **Note:** `workHistory` and `education` arrays are present in the output schema but will be **empty** — this actor does not scrape individual LinkedIn profile pages. Those fields are reserved for future enhancement. --- ### Pricing - **Model:** Pay Per Event (PPE) - **Price:** **$0.05 per profile result** - **What counts as an event:** Each profile that is found, enriched, and saved to the dataset counts as one event. - **What does NOT count:** Metadata, errors, retries, and empty results. --- ### Data Accuracy - **Names & URLs** are extracted from search result snippets — accuracy depends on search engine indexing. - **Email addresses** are **estimated** using common corporate patterns (firstname.lastname@company.com, etc.) and **must be independently verified** before use. - **Fit scores** are algorithmic keyword overlap estimates — **not** human judgment or AI reasoning. - **Work history, education, and skills** are NOT scraped from individual profile pages. Skills will only be populated if provided via the `skills` input parameter. - This tool does **not** access LinkedIn's private API or any authenticated LinkedIn data. --- ### Changelog See [CHANGELOG.md](./CHANGELOG.md) for version history. # Actor input Schema ## `searchQueries` (type: `array`): List of search strings to find candidates (e.g., ['Senior Software Engineer', 'Data Scientist']). At least one is required. ## `jobTitle` (type: `string`): Filter results by specific job title (optional). ## `location` (type: `string`): Filter results by geographic location (e.g., 'San Francisco', 'New York'). ## `company` (type: `string`): Filter results by current or past company name. Also used for email estimation. ## `skills` (type: `string`): Comma-separated list of skills to filter by (e.g., 'Python, AWS, Kubernetes'). ## `jobDescription` (type: `string`): Optional job description text. Each profile will receive an algorithmic fit score (0-100) based on keyword overlap with this text. ## `maxResults` (type: `integer`): Maximum number of profiles to return (1-1000). Capped at 1000 for cost control. ## `enrichEmail` (type: `boolean`): Estimate email addresses based on common corporate patterns. ## `verifyEmail` (type: `boolean`): Attempt to verify estimated emails via external API (requires enrichEmail=true). Results marked as 'verified', 'unverified', or 'estimated'. ## `emailVerificationApiKey` (type: `string`): Optional: Your AbstractAPI email validation API key. If not provided, falls back to Disify free API (less reliable). Required for production email verification. ## `searchMode` (type: `string`): Strategy for finding profiles. ## `delayBetweenRequests` (type: `number`): Seconds to wait between HTTP requests for politeness. Default: 2. ## `outputFormat` (type: `string`): Format for bulk export. Data is always saved to Apify dataset; this controls the downloadable file format. ## Actor input object example ```json { "searchQueries": [ "Senior Software Engineer" ], "maxResults": 25, "enrichEmail": true, "verifyEmail": false, "searchMode": "googleDork", "delayBetweenRequests": 2, "outputFormat": "json" } ```` # Actor output Schema ## `name` (type: `string`): Full name extracted from profile URL ## `firstName` (type: `string`): First name ## `lastName` (type: `string`): Last name ## `headline` (type: `string`): Professional headline / search query ## `location` (type: `string`): Geographic location ## `currentCompany` (type: `string`): Current employer ## `currentTitle` (type: `string`): Current job title ## `url` (type: `string`): LinkedIn profile URL ## `estimatedEmail` (type: `string`): Estimated email address (not verified unless emailStatus is 'verified') ## `emailConfidence` (type: `string`): Confidence level of email estimate ## `emailStatus` (type: `string`): Verification status of email ## `fitScore` (type: `string`): Algorithmic relevance score (0-100) ## `skills` (type: `string`): List of skills from search input ## `workHistory` (type: `string`): Work history entries (currently empty — full profile scraping not included) ## `education` (type: `string`): Education entries (currently empty — full profile scraping not included) ## `searchQuery` (type: `string`): The search query that found this profile ## `extractedAt` (type: `string`): Timestamp when the profile was processed # 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 = { "searchQueries": [ "Senior Software Engineer" ], "searchMode": "googleDork", "outputFormat": "json" }; // Run the Actor and wait for it to finish const run = await client.actor("fixitfoundry/linkedin-recruiter-pro").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 = { "searchQueries": ["Senior Software Engineer"], "searchMode": "googleDork", "outputFormat": "json", } # Run the Actor and wait for it to finish run = client.actor("fixitfoundry/linkedin-recruiter-pro").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 '{ "searchQueries": [ "Senior Software Engineer" ], "searchMode": "googleDork", "outputFormat": "json" }' | apify call fixitfoundry/linkedin-recruiter-pro --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fixitfoundry/linkedin-recruiter-pro", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Recruiter Pro", "description": "Advanced LinkedIn profile finder with email verification, AI fit scoring, and multiple search modes. Find candidates via Google dorking, direct search, or company employee lookup.", "version": "1.0", "x-build-id": "ygV4LHSvpEqZnCagZ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fixitfoundry~linkedin-recruiter-pro/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fixitfoundry-linkedin-recruiter-pro", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/fixitfoundry~linkedin-recruiter-pro/runs": { "post": { "operationId": "runs-sync-fixitfoundry-linkedin-recruiter-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/fixitfoundry~linkedin-recruiter-pro/run-sync": { "post": { "operationId": "run-sync-fixitfoundry-linkedin-recruiter-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "searchQueries" ], "properties": { "searchQueries": { "title": "Search Queries", "minItems": 1, "type": "array", "description": "List of search strings to find candidates (e.g., ['Senior Software Engineer', 'Data Scientist']). At least one is required.", "items": { "type": "string" } }, "jobTitle": { "title": "Job Title Filter", "type": "string", "description": "Filter results by specific job title (optional)." }, "location": { "title": "Location Filter", "type": "string", "description": "Filter results by geographic location (e.g., 'San Francisco', 'New York')." }, "company": { "title": "Company Filter", "type": "string", "description": "Filter results by current or past company name. Also used for email estimation." }, "skills": { "title": "Skills Filter", "type": "string", "description": "Comma-separated list of skills to filter by (e.g., 'Python, AWS, Kubernetes')." }, "jobDescription": { "title": "Job Description (for AI Fit Scoring)", "type": "string", "description": "Optional job description text. Each profile will receive an algorithmic fit score (0-100) based on keyword overlap with this text." }, "maxResults": { "title": "Maximum Results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of profiles to return (1-1000). Capped at 1000 for cost control.", "default": 25 }, "enrichEmail": { "title": "Enrich Email", "type": "boolean", "description": "Estimate email addresses based on common corporate patterns.", "default": true }, "verifyEmail": { "title": "Verify Email", "type": "boolean", "description": "Attempt to verify estimated emails via external API (requires enrichEmail=true). Results marked as 'verified', 'unverified', or 'estimated'.", "default": false }, "emailVerificationApiKey": { "title": "Email Verification API Key", "type": "string", "description": "Optional: Your AbstractAPI email validation API key. If not provided, falls back to Disify free API (less reliable). Required for production email verification." }, "searchMode": { "title": "Search Mode", "enum": [ "googleDork", "directSearch", "companyEmployees" ], "type": "string", "description": "Strategy for finding profiles.", "default": "googleDork" }, "delayBetweenRequests": { "title": "Delay Between Requests (seconds)", "minimum": 0.5, "maximum": 30, "type": "number", "description": "Seconds to wait between HTTP requests for politeness. Default: 2.", "default": 2 }, "outputFormat": { "title": "Output Format", "enum": [ "json", "csv", "jsonl" ], "type": "string", "description": "Format for bulk export. Data is always saved to Apify dataset; this controls the downloadable file format.", "default": "json" } } }, "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 } } } } } } } } } } ```