# Meinestadt Jobs Search Scraper (`alexist/meinestadt-jobs-search-scraper`) Actor Scrape job search results from Meinestadt.de with precision. Extract 48+ data fields including titles, salaries, company details, work locations, and job scan scores — perfect for job aggregators, HR platforms, and labor market analytics. - **URL**: https://apify.com/alexist/meinestadt-jobs-search-scraper.md - **Developed by:** [Alex](https://apify.com/alexist) (community) - **Categories:** Automation, Developer tools, Jobs - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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 ## Meinestadt Jobs Search Scraper: Harvest German Job Listings Efficiently --- ### What Is Meinestadt.de? Meinestadt.de is Germany's leading hyperlocal job and classified listing platform, connecting job seekers with employers across major German cities including Frankfurt, Berlin, Munich, and beyond. With hundreds of thousands of active listings spanning multiple industries and roles, Meinestadt.de is a critical source for understanding the German labor market. Manually extracting job search results is tedious and error-prone — the **Meinestadt Jobs Search Scraper** automates this process, delivering structured data from search result pages at scale. --- ### Overview The **Meinestadt Jobs Search Scraper** extracts job listings directly from Meinestadt.de search result pages, converting dynamic job cards into clean, structured records. It is ideal for: - **Job aggregators** building multi-source job databases - **HR platforms** pulling German job listings into candidate matching systems - **Market researchers** analyzing German employment trends by region and sector - **Recruiters** monitoring competitor activity and salary benchmarks - **Data scientists** building ML models on labor market data The scraper handles search result pagination automatically, respects rate limits, and returns detailed metadata including job scan scores, work time types, and industry classifications. --- ### Input Configuration The scraper accepts JSON configuration with the following parameters: ```json { "urls": [ "https://jobs.meinestadt.de/frankfurt-am-main/jk/0-15777#order=search(stelle%2Cfalse)" ], "max_items_per_url": 200, "ignore_url_failures": true } ```` | Parameter | Type | Description | |---|---|---| | `urls` | Array | Search result page URLs from Meinestadt.de (e.g., city-filtered searches). Paste full URLs including parameters. | | `max_items_per_url` | Integer | Maximum job listings to extract per URL (default: 100, max recommended: 200) | | `ignore_url_failures` | Boolean | If `true`, scraper continues if a URL fails; if `false`, run stops on error | > **Pro tip:** Meinestadt search URLs can include filters like location, job type, and salary range. Customize the base URL to pre-filter results before scraping. *** ### Output Fields Explained **Sample output** ```json { "job_id": 100012574793, "advertiser_id": 318288, "title": "Steuerfachangestellter (m/w/d) in moderner Kanzlei", "ad_type": "premium", "type": "stelle", "logo_url": "https://image-resize.meinestadt.de/image-resize/v2/resize?default=https://img.meinestadt.de/mailtemplates/images/fallback/jobs_80x80.jpg&w=80&h=80&sign=a8422700311ab7f56f666b54ba35cf516e81ed6fd57b4da76ea854bf64b93048&url=https%3A%2F%2Fimg.meinestadt.de%2Fimages%2Fs3%2F57c4a6fb63.jpg", "partner_logo_url": null, "logo_url_hq": "https://image-resize.meinestadt.de/image-resize/v2/resize?default=https://img.meinestadt.de/mailtemplates/images/fallback/jobs_80x80.jpg&w=160&h=160&sign=a8422700311ab7f56f666b54ba35cf516e81ed6fd57b4da76ea854bf64b93048&url=https%3A%2F%2Fimg.meinestadt.de%2Fimages%2Fs3%2F57c4a6fb63.jpg", "highlight_label": "Empfehlung", "company_name": "Kreh - Hofmann - Widmer Wirtschaftsprüfer und Steuerberater", "description_text": null, "description_text_full": null, "label_text": "13.07.2026", "label_color": "grey", "salary_label": "35.000 € - 55.000 €/Jahr", "job_scan_label_text": null, "job_scan_label_color": null, "work_city": "Babenhausen/Hessen", "nearest_address_url_name": "babenhausen-hessen", "distance": null, "other_work_cities_stripped": null, "mslayer_element_start_date": "13.07.2026", "detail_url": "https://jobs.meinestadt.de/babenhausen-hessen/premium?id=100012574793", "source": "RA", "work_time": "Vollzeit oder Teilzeit", "supports_https": true, "mlm_group": { "id": 7041448, "items": [ { "type": "JOB", "id": 100012574793, "paid": true, "job_type": "stelle" } ], "affiliate": 173, "component": "category" }, "d": null, "search_extension_type": "core", "divider": null, "position": 1, "seo_tags": [ { "id": 7170, "type": "BENEFIT", "tag": "Erfolgsprämien", "icon_name": "medalReward", "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 7139, "type": "BENEFIT", "tag": "Parkplatz", "icon_name": "garageCar", "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 7143, "type": "BENEFIT", "tag": "Betriebliche Altersvorsorge", "icon_name": "coinPiggybank", "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 391949, "type": "BENEFIT", "tag": "Sorgfältige Einarbeitung", "icon_name": null, "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 391947, "type": "BENEFIT", "tag": "Mobiles Arbeiten", "icon_name": null, "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 7152, "type": "BENEFIT", "tag": "Flexible Arbeitszeiten", "icon_name": "clockRounded", "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 7154, "type": "BENEFIT", "tag": "Zusätzliche Urlaubstage", "icon_name": "loungerUmbrella", "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 7156, "type": "BENEFIT", "tag": "Firmenevents", "icon_name": "drinksToasting", "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 96, "type": "SKILL", "tag": "DATEV", "icon_name": null, "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 1, "type": "SKILL", "tag": "MS Office", "icon_name": null, "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 429092, "type": "SKILL", "tag": "FIBU", "icon_name": null, "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 3042, "type": "SKILL", "tag": "Beratung", "icon_name": null, "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 437697, "type": "SOCIAL_SKILL", "tag": "Offenheit", "icon_name": null, "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 417903, "type": "SKILL", "tag": "Finanzbuchführung", "icon_name": null, "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 437676, "type": "SOCIAL_SKILL", "tag": "Teamfähigkeit", "icon_name": null, "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 1098, "type": "SKILL", "tag": "Steuerberatung", "icon_name": null, "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 2124, "type": "SKILL", "tag": "Korrespondenz", "icon_name": null, "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 437675, "type": "SOCIAL_SKILL", "tag": "Flexibilität", "icon_name": null, "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 485567, "type": "SKILL", "tag": "Geschäftskorrespondenz", "icon_name": "", "redirect_id": null, "debug": { "solr_queries": [] } }, { "id": 3004, "type": "SKILL", "tag": "Wirtschaftsprüfung", "icon_name": null, "redirect_id": null, "debug": { "solr_queries": [] } } ], "job_scan_score": null, "type_of_cost": null, "tracking_cost_type": "not_set", "default_application_type": "E-Mail", "on_watchlist": false, "profession_ids": [ 7571, 35075, 7572 ], "city_url_names": [ "babenhausen-hessen" ], "job_offer_type": "Festanstellung", "premium_work_time": null, "working_plan": null, "staffing": "Direktangebot", "industries": null, "category_trackings": [ "Recht & Steuern|Steuerfachangestellte|Steuerfachangestellte/r", "Recht & Steuern|Weitere Tätigkeiten - Recht & Steuer|Gehilfen in steuer- und wirtschaftsberatenden Berufen|Fachwirt/in - Steuer", "Recht & Steuern|Steuerfachangestellte|Fachgehilf(e/in) - steuer- und wirtschaftsberatende Berufe" ], "native_ad": true, "link_out_detail": false, "small_text": false, "debug_job_scan": null, "from_url": "https://jobs.meinestadt.de/frankfurt-am-main/jk/0-15777#order=search(stelle%2Cfalse)" } ``` The scraper returns 48 fields per job listing. Here are the key ones: #### Identification & Tracking | Field | Purpose | |---|---| | `Job ID` | Unique internal Meinestadt identifier for the posting | | `Advertiser ID` | ID of the company or recruiter posting the job | | `Position` | Sequential position in search results | | `Source` | Data source indicator | #### Job Content & Display | Field | Purpose | |---|---| | `Title` | Job title as shown in search results | | `Description Text` | Brief job summary | | `Description Text Full` | Complete job description | | `Ad Type` | Listing type (standard, premium, featured) | | `Type` | Employment type indicator | | `Highlight Label` | Featured or highlight badge (if applicable) | | `Label Text` | Additional label or tag | | `Label Color` | Color coding for visual categorization | #### Compensation & Work Details | Field | Purpose | |---|---| | `Salary Label` | Displayed salary range or "Salary on request" | | `Work Time` | Employment duration (full-time, part-time, contract, temporary) | | `Premium Work Time` | Premium or specialized work arrangement | | `Working Plan` | Work schedule type | | `Staffing` | Number of positions or staffing level | | `Job Offer Type` | Internal classification (e.g., permanent, temporary) | #### Location & Geography | Field | Purpose | |---|---| | `Work City` | Primary work location city | | `Other Work Cities Stripped` | Additional work locations (if multi-location) | | `Nearest Address URL Name` | Formatted location for URL | | `Distance` | Radius or distance filter applied | | `City URL Names` | URL-encoded city names for filtering | #### Company & Branding | Field | Purpose | |---|---| | `Company Name` | Employer or recruiting company name | | `Logo URL` | Company logo image URL | | `Partner Logo URL` | Partner/agency logo if applicable | | `Logo URL HQ` | High-quality version of company logo | #### Quality & Scoring | Field | Purpose | |---|---| | `Job Scan Label Text` | Meinestadt job quality score label | | `Job Scan Label Color` | Visual indicator for job quality | | `Job Scan Score` | Numeric quality metric (higher = better match) | | `Debug Job Scan` | Debug information for scoring system | #### Classification & Metadata | Field | Purpose | |---|---| | `Industries` | Industry categories (e.g., IT, Healthcare, Retail) | | `Profession IDs` | Profession classification codes | | `Category Trackings` | Internal category tracking identifiers | | `SEO Tags` | Search engine optimization tags | | `Search Extension Type` | Extended search parameter type | #### Additional Flags & Details | Field | Purpose | |---|---| | `Detail URL` | Direct link to the full job posting | | `Supports HTTPS` | Security protocol support indicator | | `MLM Group` | Multi-level classification group | | `Mslayer Element Start Date` | Platform metadata timestamp | | `Native Ad` | Whether listing is a native advertisement | | `Link Out Detail` | External link details | | `On Watchlist` | Watchlist status indicator | | `Small Text` | Micro-copy or disclaimer text | | `Divider` | Structural separator indicator | | `D` | Internal code field | | `Default Application Type` | Primary method to apply | | `Type Of Cost` | Fee structure (free, paid) | | `Tracking Cost Type` | Cost tracking classification | *** ### How to Use 1. **Find search URLs** — Go to Meinestadt.de, apply filters (city, job type, salary), and copy the resulting search URL. 2. **Prepare input** — Paste the full URL (including filter parameters) into the `urls` array. 3. **Set limits** — Configure `max_items_per_url` based on your needs (100–200 recommended for balanced speed/completeness). 4. **Run scraper** — Start the actor and monitor progress in the log. 5. **Export data** — Download results as JSON, CSV, or Excel. **Best practices:** - Use city-specific or keyword-filtered searches to reduce URL load - Set `ignore_url_failures: true` for production runs to handle network hiccups - Filter results post-scrape by `Job Scan Score` to prioritize high-quality listings - Respect Meinestadt.de's Terms of Service regarding data reuse *** ### Applications & Business Value - **Job board aggregation:** Combine German, European, and global listings into a unified platform - **Salary benchmarking:** Analyze compensation trends across industries and regions - **Talent pipeline:** Build candidate sourcing databases for recruitment automation - **Market intelligence:** Track hiring volume and skill demand shifts in real-time - **Academic research:** Study employment patterns, wage inequality, and labor mobility in Germany The Meinestadt Jobs Search Scraper eliminates hours of manual copying, enabling data-driven recruitment and labor market insights. *** ### Conclusion The **Meinestadt Jobs Search Scraper** is the go-to solution for extracting German job listings at scale. With 48+ rich data fields, intelligent job quality scoring, and flexible filtering options, it transforms Meinestadt search results into actionable business intelligence. Start scraping today and unlock the full potential of Germany's largest hyperlocal job market. # Actor input Schema ## `urls` (type: `array`): Add the URLs of the Jobs list urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list. ## `ignore_url_failures` (type: `boolean`): If true, the scraper will continue running even if some URLs fail to be scraped. ## `max_items_per_url` (type: `integer`): The maximum number of items to scrape per URL. ## Actor input object example ```json { "urls": [ "https://jobs.meinestadt.de/frankfurt-am-main/jk/0-15777#order=search(stelle%2Cfalse)" ], "ignore_url_failures": true, "max_items_per_url": 100 } ``` # 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 = { "urls": [ "https://jobs.meinestadt.de/frankfurt-am-main/jk/0-15777#order=search(stelle%2Cfalse)" ], "ignore_url_failures": true, "max_items_per_url": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("alexist/meinestadt-jobs-search-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 = { "urls": ["https://jobs.meinestadt.de/frankfurt-am-main/jk/0-15777#order=search(stelle%2Cfalse)"], "ignore_url_failures": True, "max_items_per_url": 100, } # Run the Actor and wait for it to finish run = client.actor("alexist/meinestadt-jobs-search-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 '{ "urls": [ "https://jobs.meinestadt.de/frankfurt-am-main/jk/0-15777#order=search(stelle%2Cfalse)" ], "ignore_url_failures": true, "max_items_per_url": 100 }' | apify call alexist/meinestadt-jobs-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=alexist/meinestadt-jobs-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Meinestadt Jobs Search Scraper", "description": "Scrape job search results from Meinestadt.de with precision. Extract 48+ data fields including titles, salaries, company details, work locations, and job scan scores — perfect for job aggregators, HR platforms, and labor market analytics.", "version": "0.0", "x-build-id": "Z9oZXsWfnKaNMcZN6" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/alexist~meinestadt-jobs-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-alexist-meinestadt-jobs-search-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/alexist~meinestadt-jobs-search-scraper/runs": { "post": { "operationId": "runs-sync-alexist-meinestadt-jobs-search-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/alexist~meinestadt-jobs-search-scraper/run-sync": { "post": { "operationId": "run-sync-alexist-meinestadt-jobs-search-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", "properties": { "urls": { "title": "URLs of the Jobs list urls to scrape", "type": "array", "description": "Add the URLs of the Jobs list urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list.", "items": { "type": "string" } }, "ignore_url_failures": { "title": "Continue running even if some URLs fail to be scraped", "type": "boolean", "description": "If true, the scraper will continue running even if some URLs fail to be scraped." }, "max_items_per_url": { "title": "Max items per URL", "type": "integer", "description": "The maximum number of items to scrape per URL." } } }, "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 } } } } } } } } } } ```