# Metrocuadrado Property Search Scraper (`stealth_mode/metrocuadrado-property-search-scraper`) Actor Scrape rental and sale property listings from MetroCuadrado.com with comprehensive data including prices, locations, contact info, and 40+ property details. Perfect for real estate analysts, investors, and market researchers seeking structured property data at scale. - **URL**: https://apify.com/stealth\_mode/metrocuadrado-property-search-scraper.md - **Developed by:** [Stealth mode](https://apify.com/stealth_mode) (community) - **Categories:** Automation, Developer tools, Real estate - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.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 ## MetroCuadrado Property Scraper: Extract Real Estate Listings Instantly --- ### What Is MetroCuadrado? MetroCuadrado.com is Latin America's largest real estate marketplace, hosting hundreds of thousands of active property listings for sales and rentals across multiple countries. Whether you're searching for apartments, houses, commercial spaces, or land, the platform connects buyers, sellers, and renters with verified real estate agents and direct owners. Extracting and analyzing this data manually is tedious — the **MetroCuadrado Property Scraper** automates the collection process, delivering structured, analysis-ready property data from search results. --- ### Overview The **MetroCuadrado Property Search Scraper** extracts property listings from MetroCuadrado.com search results pages, converting raw HTML into clean, structured records. It is ideal for: - **Real estate investors** tracking market trends and property availability - **Data analysts** building property datasets for market research - **Aggregator platforms** feeding property data into comparison tools - **Researchers** studying housing markets and price dynamics - **Real estate agents** monitoring competitor listings and market positioning Key features include configurable item limits per search URL, automatic handling of failed URLs, and comprehensive property metadata covering prices, locations, amenities, and contact information. --- ### Input Format The scraper accepts a JSON configuration object: ```json { "urls": [ "https://www.metrocuadrado.com/inmuebles/arriendo/?search=form" ], "ignore_url_failures": true, "max_items_per_url": 200 } ```` | Field | Description | |---|---| | `urls` | MetroCuadrado property search result URLs (e.g., rental listings by city, type, or price range) | | `max_items_per_url` | Maximum number of properties to extract per URL (e.g., `200`) | | `ignore_url_failures` | If `true`, the scraper continues running even if some URLs fail, preventing interruptions during bulk scrapes | > **Tip:** You can filter MetroCuadrado search URLs by city, property type, rental/sale, price range, and other criteria before scraping. Each URL passed to the scraper will be processed independently. *** ### Output Format **Sample output** ```json { "contact_phone": "3234808687", "whatsapp": "573234808687", "title": "Casa en Venta, CIUDAD DEL SUR, Puerto Tejada", "link": "/proyecto/casas-de-la-vega/16747-C0015-01", "image_link": "https://multimedia.metrocuadrado.com/16747-C0015-01/16747-C0015-01_1_V1_p.jpg", "whatsapp_message": "Hola, estoy interesado en el anuncio con ID: 16747-C0015-01 que encontré en Metrocuadrado. Casa en Venta, CIUDAD DEL SUR, Puerto Tejada https://www.metrocuadrado.com", "badge": "Proyecto de vivienda", "area_privada": 39.24, "midinmueble": "16747-C0015-01", "mtipoinmueble": { "id": "2", "nombre": "Casa" }, "mtiponegocio": "Venta", "mvalorventa": 169433000, "mvalorarriendo": null, "marea": 53.41, "mareac": 53.41, "areaprivada": 39.24, "mnrocuartos": "2", "mnrobanos": "1", "mnrogarajes": "1", "mciudad": { "id": "4778", "nombre": "Puerto Tejada" }, "ptags": null, "mzona": null, "mbarrio": "CIUDAD DEL SUR", "mnombrecomunbarrio": "CIUDAD DEL SUR", "data": { "mprimerafotoinmueble": "16747-C0015-01_1_V1", "murldetalle": "/proyecto/casas-de-la-vega/16747-C0015-01" }, "mnombreproyecto": "CASAS DE LA VEGA", "midempresa": "7331", "mcontactoinmobiliaria_fijo1": null, "ubicacionaproximada": null, "mestadoinmueble": "Nuevo", "mcontactosucursal_celular1": null, "mgrupoid": "02", "morden": null, "moferente": "Builder", "signwall": null, "haswhatsappbot": null, "mgaleriainmueble": [ "16747-C0015-01_1_V1", "16747-C0015-01_2_V1", "16747-C0015-01_3_V1" ], "haswhatsappotp": null, "cobertura": [], "packages": null, "tipovivienda": "VIS", "feria": null, "mnumero_contactos": null, "comment": "Casas de la Vega es un proyecto de interés social ubicado en Ciudad del Sur, a 10 minutos de Cali en el km 10 Vía Puerto Tejada. Esta ciudadela cuenta con una planeación ordenada y pensada en brindar a sus habitantes todos los beneficios de una gran ciudad, cuenta con todos los servicios públicos, amplias vías y espacios para el disfrute de las familias", "featured": [ "conCocinaIntegral:S", " conZonaLavanderia:S", " garajeConServidumbre:S", " nroBanos:1", " nroCuartos:2", " nroGarajes:1", " tipoCalentador:No tiene", " tipoCocina:Abierta", " tipoDeposito:0", " tipoEstufa:Gas" ], "categoria": null, "estrato": 3, "geopoints": null, "distance": null, "localizacion": { "lon": -76.415465, "lat": 3.220591 }, "owner_type": "Constructora", "from_url": "https://www.metrocuadrado.com/inmuebles/venta/?search=form" } ``` Each scraped property record returns 46+ fields with comprehensive details: #### Property Identification & Links | Field | Meaning | |---|---| | `Title` | Property listing title as displayed on MetroCuadrado | | `Link` | Direct URL to the property detail page | | `Image Link` | URL of the primary property image | | `ID Empresa` | Unique company/agency identifier | | `Grupo ID` | Group identifier for related listings | | `Orden` | Listing order or ranking | #### Property Type & Category | Field | Meaning | |---|---| | `Mtipo Inmueble` | Property type (apartment, house, commercial, land, etc.) | | `Mtipo Negocio` | Transaction type (rent, sale, or both) | | `Tipo Vivienda` | Housing category (residential, commercial, etc.) | | `Categoría` | Listing category classification | | `Estado Inmueble` | Property condition (new, used, renovation, etc.) | #### Pricing & Financial Terms | Field | Meaning | |---|---| | `Mvalor Venta` | Sale price in local currency | | `Mvalor Arriendo` | Monthly rental price | | `Packages` | Available listing packages or promotional options | #### Property Specifications | Field | Meaning | |---|---| | `Midinmueble` | Total property size/dimensions | | `Area Privada` | Private/indoor area in square meters | | `Areaprivada` | Additional private area specification | | `Marea` | Constructed area details | | `Mareac` | Additional area measurement | | `Número Cuartos` | Number of bedrooms | | `Número Baños` | Number of bathrooms | | `Número Garajes` | Number of garage/parking spaces | | `Estrato` | Socioeconomic stratum classification (Colombian standard) | | `Cobertura` | Coverage or amenities included | #### Location & Geographic Details | Field | Meaning | |---|---| | `Ciudad` | City where the property is located | | `Zona` | Zone or region within the city | | `Barrio` | Neighborhood name | | `Nombre Común Barrio` | Common neighborhood name used locally | | `Ubicación Aproximada` | Approximate address or location description | | `Localización` | Full location details | | `Geopoints` | GPS coordinates or geographic data | | `Distance` | Distance to key landmarks or city center | #### Contact & Communication | Field | Meaning | |---|---| | `Contact Phone` | Primary contact telephone number | | `WhatsApp` | WhatsApp contact number for inquiries | | `WhatsApp Message` | Pre-formatted WhatsApp message template | | `Has WhatsApp Bot` | Whether the listing supports WhatsApp bot interactions | | `Has WhatsApp OTP` | OTP (One-Time Password) verification via WhatsApp | | `Contacto Inmobiliaria Fijo 1` | Real estate agency landline phone | | `Contacto Sucursal Celular 1` | Branch office mobile number | | `Número Contactos` | Total number of contact options available | | `Oferente` | Offering party (agency, owner, etc.) | #### Listing Features & Status | Field | Meaning | |---|---| | `Badge` | Special badges (VIP, featured, verified, etc.) | | `PTags` | Product tags or special labels | | `Featured` | Whether the listing is featured or promoted | | `Signwall` | Signwall or virtual tour availability | | `Feria` | Fair or promotional event flag | | `Nombre Proyecto` | Project name if part of a development | #### Additional Metadata | Field | Meaning | |---|---| | `Owner Type` | Type of owner (individual, agency, developer, etc.) | | `Data` | Additional data or metadata field | | `Galería Inmueble` | Links to full property image gallery | | `Comment` | Remarks or special notes about the property | *** ### How to Use 1. **Build search URLs** — Navigate to MetroCuadrado.com and filter for properties by city, type, price, bedrooms, or other criteria. Copy the search result URL. 2. **Add URLs to input** — Paste one or multiple search URLs into the `urls` array. 3. **Set scrape limits** — Configure `max_items_per_url` (e.g., `200` for comprehensive scrapes or `50` for quick tests). 4. **Enable error handling** — Keep `ignore_url_failures: true` to handle temporary network issues without stopping the run. 5. **Run and export** — Start the scraper and download results as JSON, CSV, or Excel once complete. **Common tips:** - Narrower search filters (by city, price range, or property type) yield faster, more targeted results. - Use `max_items_per_url: 200` to capture most listings per search page. - WhatsApp and phone contact fields enable direct outreach to agents or owners. *** ### Use Cases & Business Value - **Market analysis:** Track property prices, availability, and trends by neighborhood or city - **Investment research:** Identify underpriced properties or emerging real estate markets - **Competitive intelligence:** Monitor competitor agents' listings and pricing strategies - **Data aggregation:** Build a unified property database from MetroCuadrado for comparison platforms - **Lead generation:** Export contact information for real estate outreach campaigns - **Academic research:** Analyze housing supply, demand, and affordability patterns The MetroCuadrado Property Scraper converts thousands of unstructured listings into actionable data, saving weeks of manual research and unlocking insights that drive smarter real estate decisions. *** ### Conclusion The **MetroCuadrado Property Search Scraper** is an essential tool for anyone working with Latin American real estate data. With 46+ structured fields per property and flexible search URL configuration, it enables rapid, large-scale data collection without manual browsing. Extract property details, contact information, pricing, and location data in minutes — then analyze, aggregate, or share the results with confidence. # Actor input Schema ## `urls` (type: `array`): Add the URLs of the property 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://www.metrocuadrado.com/inmuebles/arriendo/?search=form" ], "ignore_url_failures": true, "max_items_per_url": 20 } ``` # 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://www.metrocuadrado.com/inmuebles/arriendo/?search=form" ], "ignore_url_failures": true, "max_items_per_url": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("stealth_mode/metrocuadrado-property-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://www.metrocuadrado.com/inmuebles/arriendo/?search=form"], "ignore_url_failures": True, "max_items_per_url": 20, } # Run the Actor and wait for it to finish run = client.actor("stealth_mode/metrocuadrado-property-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://www.metrocuadrado.com/inmuebles/arriendo/?search=form" ], "ignore_url_failures": true, "max_items_per_url": 20 }' | apify call stealth_mode/metrocuadrado-property-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=stealth_mode/metrocuadrado-property-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Metrocuadrado Property Search Scraper", "description": "Scrape rental and sale property listings from MetroCuadrado.com with comprehensive data including prices, locations, contact info, and 40+ property details. Perfect for real estate analysts, investors, and market researchers seeking structured property data at scale.", "version": "0.0", "x-build-id": "WHDbcqhdBFBQx64Uc" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/stealth_mode~metrocuadrado-property-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-stealth_mode-metrocuadrado-property-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/stealth_mode~metrocuadrado-property-search-scraper/runs": { "post": { "operationId": "runs-sync-stealth_mode-metrocuadrado-property-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/stealth_mode~metrocuadrado-property-search-scraper/run-sync": { "post": { "operationId": "run-sync-stealth_mode-metrocuadrado-property-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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 property list urls to scrape", "type": "array", "description": "Add the URLs of the property 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 } } } } } } } } } } ```