# LinkedIn Recruiter Scraper 🔎 Find Recruiters & Hiring Managers (`apt_marble/linkedin-recruiter-scraper`) Actor Find recruiters, hiring managers, and talent acquisition specialists from public LinkedIn profiles by keyword, industry, and location 🚀 Extract recruiter names, companies, locations, hiring niches, and profile URLs with clean structured data- no LinkedIn login or cookies required. - **URL**: https://apify.com/apt\_marble/linkedin-recruiter-scraper.md - **Developed by:** [Hamza](https://apify.com/apt_marble) (community) - **Categories:** Lead generation, Automation, Jobs - **Stats:** 12 total users, 6 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $2.50 / 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 Scraper **Find recruiters, hiring managers, technical recruiters, and talent acquisition specialists from public LinkedIn profiles — by industry, technology, and location. No cookies, no LinkedIn login, no Sales Navigator seat required.** Paste the recruiter titles you want, optionally narrow by tech stack or industry, and walk away with a clean spreadsheet of names, current titles, companies, locations, and a detected **hiring niche** for every profile — ready for your CRM, outreach sequencer, or your "who's hiring React engineers right now" list. --- ### What it does This actor turns LinkedIn into a recruiter-discovery engine. Specify the titles you care about (`Recruiter`, `Technical Recruiter`, `Talent Acquisition Manager`, `Hiring Manager`, …), optionally add tech keywords (`React`, `Python`, `AI`) or industries (`Healthcare`, `Fintech`, `SaaS`), and it returns a structured list of matching profiles plus an inferred hiring specialization for each. Marketed as: **"Find Recruiters & Hiring Managers from LinkedIn — by industry, tech stack, and location."** --- ### Who uses this **Job seekers** — Find every recruiter hiring for React, Python, or AI roles in your city. Skip the cold-outreach guesswork — message the people whose actual job is to fill the role. **Staffing agencies** — Map the in-house recruiting teams at target accounts. Spot understaffed TA teams that are good acquisition targets. **Outreach agencies & sales reps** — Build clean, segmented lists of HR / TA leaders to pitch HRTech products to. **HR SaaS founders** — Generate ICP lists by niche (`AI recruiters`, `healthcare recruiters`, `fintech recruiters`) for product-led growth and webinar invites. **Recruiting tool comparison & competitive intel** — See which recruiters at competing firms specialize in your domain. **Investors** — Track hiring intent at portfolio companies by industry vertical. --- ### What you get back Each row in the dataset is one recruiter: ```json { "fullName": "Sarah Johnson", "firstName": "Sarah", "lastName": "Johnson", "currentTitle": "Technical Recruiter", "company": "TechHire Solutions", "hiringNiche": "Frontend Developers", "linkedinUrl": "https://www.linkedin.com/in/sarahjohnson", "profileImage": null, "snippet": "Technical recruiter focused on hiring React developers and AI engineers...", "matchedKeyword": "React", "recruiterTitleMatched": "Technical Recruiter", "locationKeyword": "Germany", "timestamp": "2026-05-22T12:00:00Z" } ```` The full field list: | Field | What it is | |---|---| | `fullName` | The recruiter's full name | | `firstName` / `lastName` | Best-effort split for mail-merge | | `currentTitle` | Detected current title (Recruiter, Technical Recruiter, TA Manager, …) | | `company` | Current company | | `hiringNiche` | Inferred specialization (e.g. "Frontend Developers", "AI / ML Talent") | | `linkedinUrl` | Canonical `https://www.linkedin.com/in/` URL | | `snippet` | Raw profile snippet text | | `matchedKeyword` | The industry / tech keyword that surfaced the profile | | `recruiterTitleMatched` | Which recruiter-title bucket the profile matched | | `locationKeyword` | The location filter used (if any) | | `timestamp` | ISO 8601 scrape time | Export to CSV, JSON, Excel, or pipe directly into Zapier, Make, Clay, Apollo, or any HTTP webhook. *** ### Inputs | Field | Type | What it does | |---|---|---| | **Recruiter Titles** | `array` | Titles to hunt for. Defaults to `Recruiter, Technical Recruiter, Talent Acquisition`. Add `Hiring Manager`, `Staffing Specialist`, `Recruiting Lead`, `Head of Recruitment`, `Recruitment Consultant`, etc. | | **Industry / Tech Keywords** | `array` | Niche filters (`React`, `Python`, `AI`, `SaaS`, `Healthcare`, `Fintech`, `Cybersecurity`). Optional. | | **Locations** | `array` | Country / region / city filters (`United States`, `Berlin`, `Dubai`). Optional. | | **Maximum Profiles** | `integer` | Stop after collecting N unique profiles. Default `100`. | | **Search Language** | `string` | Language hint. Default `en`. | | **Deduplicate Results** | `boolean` | Drop duplicate LinkedIn URLs across the run. Default `true`. | The actor expands every (keyword × location) combination using the supplied title bucket. So 3 tech keywords × 2 locations = 6 internal searches, all deduplicated into one clean dataset. *** ### Hiring-niche detection Each profile gets a `hiringNiche` label inferred from the keyword you searched, the LinkedIn headline, and the snippet text. A non-exhaustive list of the buckets: | Trigger words | Detected niche | |---|---| | `React`, `Vue`, `Angular`, `Svelte`, `frontend` | **Frontend Developers** | | `Python`, `Django`, `FastAPI` | **Python Engineers** | | `Java`, `Spring Boot`, `Kotlin` | **Java / JVM Engineers** | | `Golang`, `Rust`, `C++` | **Systems Engineers** | | `Node.js`, `TypeScript`, `full-stack` | **Full-Stack Engineers** | | `iOS`, `Swift`, `Android`, `Flutter`, `React Native` | **Mobile Engineers** | | `DevOps`, `SRE`, `Kubernetes`, `Terraform`, `AWS`, `GCP`, `Azure` | **DevOps / Cloud Engineers** | | `Data engineer`, `Data scientist`, `Snowflake`, `Databricks` | **Data Engineers** | | `AI`, `ML`, `LLM`, `Generative AI`, `NLP`, `Computer Vision` | **AI / ML Talent** | | `Cybersecurity`, `InfoSec`, `Pentest`, `SOC Analyst` | **Security Professionals** | | `UX`, `UI`, `Product Design`, `Figma` | **Design Talent** | | `Healthcare`, `Medical`, `Pharma`, `Biotech` | **Medical / Healthcare Hiring** | | `Fintech`, `Banking`, `Asset Management`, `Trading` | **Finance Industry** | | `SaaS`, `B2B SaaS` | **SaaS Hiring** | | `Shopify`, `E-commerce`, `Retail`, `Marketplace` | **E-commerce Hiring** | | `Marketing`, `Growth`, `SEO`, `SEM` | **Marketing Talent** | | `Sales`, `Account Executive`, `BDR`, `SDR` | **Sales Talent** | | `Blockchain`, `Crypto`, `Web3`, `Solidity` | **Web3 / Crypto Talent** | If you typed a keyword that's not in the rule list, the actor still surfaces it as ` Hiring` so the field is never empty when you asked for something specific. *** ### Example use cases **Job seekers** — `recruiterTitles: ["Technical Recruiter", "Talent Acquisition"]`, `keywords: ["React"]`, `locations: ["Berlin", "London"]`. Result: every TA pro hiring React talent in Berlin and London, with a `hiringNiche: "Frontend Developers"` tag. **Staffing agency prospecting** — `recruiterTitles: ["Head of Recruitment", "Talent Acquisition Manager"]`, `keywords: ["SaaS"]`, `locations: ["United States"]`. Pull every in-house TA leader at US SaaS companies and pitch your staffing services. **HRTech sales** — `recruiterTitles: ["Recruiter"]`, `keywords: ["Healthcare", "Pharma", "Biotech"]`, `locations: ["United States", "Germany"]`. Build an ICP list for a recruiting product targeting healthcare HR. **Outbound to in-house recruiters** — `recruiterTitles: ["Technical Recruiter"]`, `keywords: ["AI", "ML"]`. Find everyone hiring AI/ML engineers, then enrich emails via Clay or Apollo. *** ### Tips that save you time and money - **Preview with a low cap.** Set `Maximum Profiles` to 25 for your first run to verify the queries return the kind of recruiters you expect. - **Niche detection works best when you supply a keyword.** Searching `recruiter` alone returns a generic bucket. Adding `React` or `Healthcare` lights up the `hiringNiche` field for everyone the keyword matched. - **Stack multiple title buckets in one run.** `["Technical Recruiter", "Talent Acquisition", "Hiring Manager"]` runs faster than three separate runs because the start fee is charged once. - **Locations are loose by design** — they're matched as phrases that appear anywhere on the profile, so you'll get some noise. Run per-country if you need clean segmentation. - **Deduplication is on by default.** Leave it on unless you specifically want to see overlap across keywords. *** ### Pricing — pay only for what you extract | Apify Plan | Start Fee | Per Profile | | ------------- | --------- | ----------- | | Free / Bronze | $0.0025 | $0.0025 | | Silver | $0.0025 | ~$0.0022 | | Gold | $0.0025 | ~$0.0020 | | Platinum | $0.0025 | ~$0.0018 | | Diamond | $0.0025 | ~$0.0015 | Affordable lead generation at scale without expensive LinkedIn tools 🚀 - 25 recruiters for a test run: about **$0.06** - 250 React recruiters across the US & Canada: **$0.63** - 2,000 recruiters across 10 niches: about **$5.00** *** ### Frequently asked **Do I need a LinkedIn account or Sales Navigator?** No. The actor never logs into LinkedIn, never asks for cookies, and never touches your account. It returns publicly visible profile data only. **Will this get me LinkedIn-banned?** No. There's no account activity for LinkedIn to flag. **How accurate is the `hiringNiche` field?** The detector matches against ~20 niche buckets covering frontend, backend, DevOps, data, AI/ML, security, design, healthcare, fintech, marketing, sales, Web3, and more. If you searched with an explicit keyword (`React`, `Pharma`, …), expect 80%+ accuracy. If you searched with no keyword, the field will often be null because there's no signal to classify on. **Will I get duplicates if I run it twice?** Within a single run, no — dedup is on by default. Across runs, yes — track previously seen `linkedinUrl` values in your own pipeline. **Can I schedule this?** Yes. Apify Schedules let you run it weekly to catch new recruiters entering an industry or location. **The actor returned 0 results — what's wrong?** (1) Try removing the `Locations` filter to see if the issue is over-narrowing. (2) Broaden your title list — add `Recruiter` alongside `Talent Acquisition`. (3) Use a more common keyword (`SaaS` instead of `Vertical SaaS`). *** ### A note on responsible use This actor extracts data that is already publicly visible on LinkedIn. It does not bypass authentication, log into accounts, scrape private profiles, or pull anything beyond what any anonymous visitor could see. The legal foundation for scraping public profile data was reinforced in **hiQ Labs v. LinkedIn** (9th Circuit, 2022). That said: **scraped data is still personal data**. Don't use it for spam, harassment, or anything that violates GDPR, CCPA, or similar laws in your jurisdiction. Treat the recruiters in your dataset like the experienced humans they are — they'll notice cold-blast outreach immediately. *** ### Drop it into your workflow - **Apify Schedules** → run weekly to surface new recruiters joining your niche - **Zapier / Make** → push new rows into HubSpot, Salesforce, Notion, or Google Sheets - **Apify Webhook** → POST results to your server for custom enrichment - **Pair with a LinkedIn Profile Scraper** → use `linkedinUrl` to enrich each recruiter with full work history - **Pair with an email-finder** → push `firstName + lastName + company` into Clay, Apollo, or Hunter to resolve emails Run it once with a small `maxResults` to see what you get. The first 25 profiles are usually cheap enough to taste-test before committing. # Actor input Schema ## `recruiterTitles` (type: `array`): Recruiter-related titles to search for. Common picks: Recruiter, Technical Recruiter, Talent Acquisition, Talent Acquisition Manager, HR Recruiter, Hiring Manager, Staffing Specialist, Recruiting Lead, Head of Recruitment, Recruitment Consultant. ## `keywords` (type: `array`): Industry tags (`SaaS`, `Healthcare`, `Fintech`, `Cybersecurity`, `E-commerce`) or technologies (`React`, `Python`, `AI`, `Go`, `Kubernetes`). Used to find recruiters who specialize in those niches. Leave empty to skip keyword filtering. ## `locations` (type: `array`): Country, region, or city filters. Examples: `United States`, `Canada`, `Germany`, `Dubai`, `London`. Leave empty to search worldwide. ## `maxResults` (type: `integer`): Stop after collecting this many unique recruiter profiles. ## `language` (type: `string`): Language hint for the search (`en`, `fr`, `de`, `es`, `pt`, etc.). ## `deduplicateResults` (type: `boolean`): Drop duplicate profiles based on the canonical LinkedIn URL. ## Actor input object example ```json { "recruiterTitles": [ "Recruiter", "Technical Recruiter", "Talent Acquisition" ], "keywords": [ "SaaS" ], "locations": [ "United States" ], "maxResults": 100, "language": "en", "deduplicateResults": true } ``` # 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 = { "recruiterTitles": [ "Recruiter", "Technical Recruiter", "Talent Acquisition" ], "keywords": [ "SaaS" ], "locations": [ "United States" ] }; // Run the Actor and wait for it to finish const run = await client.actor("apt_marble/linkedin-recruiter-scraper").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 = { "recruiterTitles": [ "Recruiter", "Technical Recruiter", "Talent Acquisition", ], "keywords": ["SaaS"], "locations": ["United States"], } # Run the Actor and wait for it to finish run = client.actor("apt_marble/linkedin-recruiter-scraper").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 '{ "recruiterTitles": [ "Recruiter", "Technical Recruiter", "Talent Acquisition" ], "keywords": [ "SaaS" ], "locations": [ "United States" ] }' | apify call apt_marble/linkedin-recruiter-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=apt_marble/linkedin-recruiter-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Recruiter Scraper 🔎 Find Recruiters & Hiring Managers", "description": "Find recruiters, hiring managers, and talent acquisition specialists from public LinkedIn profiles by keyword, industry, and location 🚀 Extract recruiter names, companies, locations, hiring niches, and profile URLs with clean structured data- no LinkedIn login or cookies required.", "version": "0.0", "x-build-id": "44at5jOfAnqmkQ1Ha" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/apt_marble~linkedin-recruiter-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-apt_marble-linkedin-recruiter-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/apt_marble~linkedin-recruiter-scraper/runs": { "post": { "operationId": "runs-sync-apt_marble-linkedin-recruiter-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/apt_marble~linkedin-recruiter-scraper/run-sync": { "post": { "operationId": "run-sync-apt_marble-linkedin-recruiter-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "recruiterTitles" ], "properties": { "recruiterTitles": { "title": "🎯 Recruiter Titles", "type": "array", "description": "Recruiter-related titles to search for. Common picks: Recruiter, Technical Recruiter, Talent Acquisition, Talent Acquisition Manager, HR Recruiter, Hiring Manager, Staffing Specialist, Recruiting Lead, Head of Recruitment, Recruitment Consultant.", "default": [ "Recruiter", "Technical Recruiter", "Talent Acquisition" ], "items": { "type": "string" } }, "keywords": { "title": "Industry / Tech Keywords", "type": "array", "description": "Industry tags (`SaaS`, `Healthcare`, `Fintech`, `Cybersecurity`, `E-commerce`) or technologies (`React`, `Python`, `AI`, `Go`, `Kubernetes`). Used to find recruiters who specialize in those niches. Leave empty to skip keyword filtering.", "default": [], "items": { "type": "string" } }, "locations": { "title": "Locations", "type": "array", "description": "Country, region, or city filters. Examples: `United States`, `Canada`, `Germany`, `Dubai`, `London`. Leave empty to search worldwide.", "default": [], "items": { "type": "string" } }, "maxResults": { "title": "Maximum Profiles", "minimum": 1, "maximum": 2000, "type": "integer", "description": "Stop after collecting this many unique recruiter profiles.", "default": 100 }, "language": { "title": "Search Language", "type": "string", "description": "Language hint for the search (`en`, `fr`, `de`, `es`, `pt`, etc.).", "default": "en" }, "deduplicateResults": { "title": "Deduplicate Results", "type": "boolean", "description": "Drop duplicate profiles based on the canonical LinkedIn URL.", "default": true } } }, "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 } } } } } } } } } } ```