# Realtorca Property Scraper (`ocrad/realtorca-property-scraper`) Actor Scrapes property listings from Realtor.ca search result pages. Supports pagination and optional deep-scraping of individual listing detail pages. - **URL**: https://apify.com/ocrad/realtorca-property-scraper.md - **Developed by:** [Ocrad](https://apify.com/ocrad) (community) - **Categories:** Real estate, Automation, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $7.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ### Realtor.ca Property Scraper --- #### 🔍 **What it does** This Actor scrapes **MLS® property listings** from [Realtor.ca](https://www.realtor.ca). By providing any Realtor.ca map search URL, you can retrieve structured property data across multiple result pages. --- #### **📝 Example Output** **Basic record** (`detailedInfo: false`): ```json { "id": "29702422", "url": "https://www.realtor.ca/real-estate/29702422/33-richmond-street-brantford", "mlsNumber": "40821620", "title": "33 RICHMOND Street, Brantford, Ontario", "price": "$475,000", "address": "33 RICHMOND Street", "city": "Brantford", "province": "Ontario", "typeAndIntro": null, "availability": null, "tags": ["1 hour ago"], "imageUrl": "https://cdn.realtor.ca/listings/TS639135846646700000/reb41/medres/0/40821620_1.jpg", "bedrooms": "3", "bathrooms": "2", "squareFeet": "1248", "brokerage": "Re/Max Escarpment Realty Inc.", "scrapedAt": "2026-05-05T19:24:42.909Z" } ```` **Detailed record** (`detailedInfo: true`, additional fields): ```json { "typeAndIntro": "Residential Freehold — House", "propertySummary": { "Property Type": "Residential Freehold", "Building Type": "House", "Storeys": "1.5", "Square Footage": "1100 - 1500 sqft", "Land Size": "27 ft ,6 in x 66 ft", "Annual Property Taxes": "$2,688.69", "Parking Type": "Detached Garage" }, "featureGroups": [ { "groupName": "Interior Features", "items": [ { "label": "Appliances Included", "value": "Dryer, Stove, Washer, Refrigerator" }, { "label": "Basement Type", "value": "Full (Finished)" } ] }, { "groupName": "Heating & Cooling", "items": [ { "label": "Cooling", "value": "Central air conditioning" }, { "label": "Heating Type", "value": "Forced air (Natural gas)" } ] } ], "rooms": [ { "name": "Living Room", "storey": "Main", "dimensions": "4.57 x 3.35 m", "flooring": "Hardwood" } ], "agentNames": ["DANIEL LAMBKIN"], "officeName": "RE/MAX TWIN CITY REALTY INC.", "description": "Welcome to this beautifully maintained home..." } ``` #### ⚙️ **Configuration** | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `url` | String | *(required)* | Realtor.ca map search URL with filters pre-applied. Must contain a `#` hash with search parameters. | | `maxPages` | Integer | `1` | Number of result pages to scrape (1–1000). Each page typically contains 12–20 listings. | | `detailedInfo` | Boolean | `false` | Visit each listing's detail page for full property data (slower, more data). | ##### Example Input ```json { "url": "https://www.realtor.ca/map#view=list&CurrentPage=1&Sort=6-D&GeoIds=g30_dpwvmr78&GeoName=Brantford%2C%20ON&PropertyTypeGroupID=1&TransactionTypeId=2&PropertySearchTypeId=1&Currency=CAD", "maxPages": 5, "detailedInfo": false } ``` ##### Getting your search URL 1. Go to [realtor.ca](https://www.realtor.ca) 2. Apply your filters (location, price, property type, transaction type, etc.) 3. Switch to **List view** 4. Copy the full URL from your browser address bar — it will contain a `#` fragment with all your filters 5. Paste it as the `url` input *** #### 💬 **Support and Feedback** Need help or have suggestions? Reach out via Apify support channels or leave feedback on the Actor's page. *** #### **Is it legal to scrape Realtor.ca data?** It is legal to scrape publicly available data such as property prices, addresses, and listing details. However, you should be aware that results may contain personal information (agent names, contact details). Personal data is protected by PIPEDA (Canada) and other regulations. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, please consult your lawyers. You can also read Apify's blog post on the legality of web scraping. # Actor input Schema ## `url` (type: `string`): A Realtor.ca map search URL with your filters already applied in the browser. Must contain a hash fragment with CurrentPage= (or one will be injected). Example: https://www.realtor.ca/map#view=list\&CurrentPage=1\&Sort=6-D\&GeoIds=g30\_dpwvmr78\&GeoName=Brantford%2C%20ON\&PropertyTypeGroupID=1\&TransactionTypeId=2\&PropertySearchTypeId=1\&Currency=CAD ## `maxPages` (type: `integer`): Number of result pages to scrape (default 1, max 1000). All page URLs are pre-built upfront using CurrentPage=N in the hash fragment. ## `detailedInfo` (type: `boolean`): When enabled the actor visits each listing's detail page and extracts: property summary, grouped building features, rooms table, agent names, office, and description. Charges listing-detailed instead of listing-basic. ## Actor input object example ```json { "maxPages": 1, "detailedInfo": false } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("ocrad/realtorca-property-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 = {} # Run the Actor and wait for it to finish run = client.actor("ocrad/realtorca-property-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 '{}' | apify call ocrad/realtorca-property-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ocrad/realtorca-property-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Realtorca Property Scraper", "description": "Scrapes property listings from Realtor.ca search result pages. Supports pagination and optional deep-scraping of individual listing detail pages.", "version": "0.0", "x-build-id": "OWf7YGgmo8iGh2eyc" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ocrad~realtorca-property-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ocrad-realtorca-property-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ocrad~realtorca-property-scraper/runs": { "post": { "operationId": "runs-sync-ocrad-realtorca-property-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ocrad~realtorca-property-scraper/run-sync": { "post": { "operationId": "run-sync-ocrad-realtorca-property-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "url" ], "properties": { "url": { "title": "Search results URL", "type": "string", "description": "A Realtor.ca map search URL with your filters already applied in the browser. Must contain a hash fragment with CurrentPage= (or one will be injected). Example: https://www.realtor.ca/map#view=list&CurrentPage=1&Sort=6-D&GeoIds=g30_dpwvmr78&GeoName=Brantford%2C%20ON&PropertyTypeGroupID=1&TransactionTypeId=2&PropertySearchTypeId=1&Currency=CAD" }, "maxPages": { "title": "Max pages", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Number of result pages to scrape (default 1, max 1000). All page URLs are pre-built upfront using CurrentPage=N in the hash fragment.", "default": 1 }, "detailedInfo": { "title": "Scrape detailed info", "type": "boolean", "description": "When enabled the actor visits each listing's detail page and extracts: property summary, grouped building features, rooms table, agent names, office, and description. Charges listing-detailed instead of listing-basic.", "default": false } } }, "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 } } } } } } } } } } ```