# MagicBricks Scraper — India Real Estate Listings API (`nexgendata/india-magicbricks-real-estate`) Actor Scrape Indian property listings from MagicBricks — residential apartments, villas, plots, commercial across Mumbai, Bangalore, Delhi NCR, Pune, Hyderabad, Chennai. Filter by BHK, budget (INR), sale or rent. 99acres / Housing.com alternative for builders, brokers, NRI buyers, investors. - **URL**: https://apify.com/nexgendata/india-magicbricks-real-estate.md - **Developed by:** [NexGenData](https://apify.com/nexgendata) (community) - **Categories:** Real estate, Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $80.00 / 1,000 listings 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/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 ## MagicBricks Scraper Scrape India property listings from MagicBricks — price, area, locality and property type. > Market data for your research. Not investment, valuation or financial advice. ### ⏰ Run this as a daily price/listing watch (recommended) Prices and listings move constantly. Schedule a daily sweep (`0 7 * * *`) and track changes over time — an always-on listing feed. ### 📊 What you get Clean JSON, one record per listing (full output has 12 fields): - `id` — Id - `title` — Title - `locality` — Locality - `city` — City - `price` — Price - `price_per_sqft` — Price per sqft - `area_sqft` — Area sqft - `bedrooms` — Bedrooms - `bathrooms` — Bathrooms - `property_type` — Property type **Pricing:** $0.080 per listing (Pay-Per-Event) — about **12 listings per $1**. ### 🤖 Use with AI agents Point Claude, the OpenAI Agents SDK, an n8n flow or any MCP-aware client at it and pull data on demand. **Agentic payments (x402):** Supports agentic payment via x402 — agents can call this actor with USDC, no API key required. ### 🔗 Related actors **Global property data — listings and prices across seven markets:** [Zillow (US)](https://apify.com/nexgendata/zillow-scraper) · [Redfin (US)](https://apify.com/nexgendata/redfin-real-estate-scraper) · [Rightmove (UK)](https://apify.com/nexgendata/rightmove-uk-real-estate-scraper) · [Boliga (Denmark)](https://apify.com/nexgendata/boliga-denmark-real-estate) · [Centaline (Hong Kong)](https://apify.com/nexgendata/hk-centaline-property-index) · [Singapore URA](https://apify.com/nexgendata/sg-ura-property-transactions) · [Singapore HDB](https://apify.com/nexgendata/sg-hdb-resale-prices) **Agent front doors:** [Real Estate MCP](https://apify.com/nexgendata/real-estate-mcp-server) · [Redfin MCP](https://apify.com/nexgendata/redfin-mcp-server) *This actor is currently private — treated and ready for review.* --- *Public web data, assembled for research and monitoring.* # Actor input Schema ## `city` (type: `string`): Indian city to scrape property listings for. MagicBricks indexes 100+ Indian cities; the highest-volume markets are: Mumbai (Bandra, Andheri, Powai, Worli, Lower Parel, Thane, Navi Mumbai), Bangalore (Whitefield, Sarjapur, Electronic City, HSR Layout, Hebbal, Yelahanka, Marathahalli, Koramangala), Delhi NCR (Gurgaon Sectors 1-115, Noida Sectors 1-168, Dwarka, South Delhi), Pune (Hinjewadi, Wakad, Baner, Kharadi, Wagholi, Kothrud), Hyderabad (Gachibowli, HITEC City, Kondapur, Madhapur, Manikonda, Kukatpally), Chennai (OMR, Velachery, Adyar, Anna Nagar, T. Nagar, Tambaram), Kolkata, Ahmedabad, Jaipur, Lucknow, Indore, Chandigarh, Coimbatore. ## `propertyType` (type: `string`): Property category. 'apartment' covers multistorey apartments / flats / builder floors — the dominant supply in Indian Tier-1 metros (Mumbai, Bangalore, Hyderabad). 'villa' covers independent houses / row houses / villas — common in Bangalore (Whitefield / Sarjapur gated communities), Gurgaon (DLF / Emaar / Sobha), and Hyderabad (Gachibowli / Tellapur). 'plot' covers residential land plots — important in Tier-2 / Tier-3 cities and outer Tier-1 (North Bangalore, Chennai OMR, outer Pune). 'commercial' covers office space, retail, shops, and showrooms — important for IT-park / SEZ / mall investment research. 'any' returns all categories. ## `listingType` (type: `string`): Whether to scrape sale listings or rent listings. Indian property buyers and brokers typically work one side: builders / developers / NRI investors focus on 'sale', while corporate housing teams and city-relocation services focus on 'rent'. Pricing schema differs — sale price is in INR (crores / lakhs), rent price is in INR / month. ## `bhk` (type: `array`): BHK = Bedroom, Hall, Kitchen — the standard Indian property bedroom-count notation. 1BHK = studio / 1-bedroom (Mumbai compact apartments, PG-friendly). 2BHK = the volume tier for young families in Bangalore / Pune / Hyderabad (60-80% of new launches). 3BHK = mid-size family unit, the upgrade tier for IT professionals. 4BHK / 5BHK+ = premium / luxury tier (sea-facing Mumbai, golf-course Gurgaon, prime South Delhi). Leave empty to span all sizes. ## `budgetMinInr` (type: `integer`): Lower bound on listing price in Indian Rupees (INR). 1 lakh = 100,000 INR; 1 crore = 10,000,000 INR. Common buyer tiers for residential SALE: 40 lakh = entry-level Tier-2 city apartment; 80 lakh = mid Bangalore / Pune 2BHK; 1.5 crore = premium Bangalore 3BHK / mid-Mumbai 2BHK; 3 crore = luxury Mumbai / Gurgaon / South Delhi tier; 10 crore+ = ultra-prime (Worli, DLF Camellias, Lutyens Delhi). For RENT listings, scales are monthly INR: 25,000 = mid Bangalore 2BHK; 80,000 = premium Mumbai; 2 lakh+ = ultra-prime serviced apartment. Set 0 for no lower bound. ## `budgetMaxInr` (type: `integer`): Upper bound on listing price in INR. Example: pass 10000000 (= 1 crore) to filter out luxury listings and focus on the mid-market / first-time buyer tier; pass 5000000 (= 50 lakh) for the entry-level affordable segment; pass 100000000 (= 10 crore) to slice the ultra-luxury market. For RENT, the same INR field is interpreted as INR / month. Set 0 for no upper bound. ## `maxResults` (type: `integer`): Hard cap on total listings returned per run (1-2000). Each listing is one MagicBricks property record. Most recent / featured listings are returned first. Premium per-listing pricing applies — Indian property data is a high-volume residential tier matching the SG Rental Market Tracker pricing standard. ## `notionConnector` (type: `string`): Optional. Connect your Notion workspace and the listings are also written as a Notion page in the same run — the Actor never sees your Notion credentials. Authorize a Notion MCP connector in Apify Console → Settings → API & Integrations, then select it here. ## `notionParentId` (type: `string`): Optional Notion page ID to create the page under. Blank = a private page in your workspace. ## Actor input object example ```json { "city": "Bangalore", "propertyType": "apartment", "listingType": "sale", "bhk": [ "2" ], "budgetMinInr": 0, "budgetMaxInr": 10000000, "maxResults": 10 } ```` # 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 = { "city": "Bangalore", "propertyType": "apartment", "listingType": "sale", "bhk": [ "2" ], "budgetMinInr": 0, "budgetMaxInr": 10000000, "maxResults": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/india-magicbricks-real-estate").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 = { "city": "Bangalore", "propertyType": "apartment", "listingType": "sale", "bhk": ["2"], "budgetMinInr": 0, "budgetMaxInr": 10000000, "maxResults": 10, } # Run the Actor and wait for it to finish run = client.actor("nexgendata/india-magicbricks-real-estate").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 '{ "city": "Bangalore", "propertyType": "apartment", "listingType": "sale", "bhk": [ "2" ], "budgetMinInr": 0, "budgetMaxInr": 10000000, "maxResults": 10 }' | apify call nexgendata/india-magicbricks-real-estate --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/india-magicbricks-real-estate", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "MagicBricks Scraper — India Real Estate Listings API", "description": "Scrape Indian property listings from MagicBricks — residential apartments, villas, plots, commercial across Mumbai, Bangalore, Delhi NCR, Pune, Hyderabad, Chennai. Filter by BHK, budget (INR), sale or rent. 99acres / Housing.com alternative for builders, brokers, NRI buyers, investors.", "version": "0.0", "x-build-id": "oAidae93CmfR0eObT" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~india-magicbricks-real-estate/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-india-magicbricks-real-estate", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~india-magicbricks-real-estate/runs": { "post": { "operationId": "runs-sync-nexgendata-india-magicbricks-real-estate", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~india-magicbricks-real-estate/run-sync": { "post": { "operationId": "run-sync-nexgendata-india-magicbricks-real-estate", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "city": { "title": "City", "type": "string", "description": "Indian city to scrape property listings for. MagicBricks indexes 100+ Indian cities; the highest-volume markets are: Mumbai (Bandra, Andheri, Powai, Worli, Lower Parel, Thane, Navi Mumbai), Bangalore (Whitefield, Sarjapur, Electronic City, HSR Layout, Hebbal, Yelahanka, Marathahalli, Koramangala), Delhi NCR (Gurgaon Sectors 1-115, Noida Sectors 1-168, Dwarka, South Delhi), Pune (Hinjewadi, Wakad, Baner, Kharadi, Wagholi, Kothrud), Hyderabad (Gachibowli, HITEC City, Kondapur, Madhapur, Manikonda, Kukatpally), Chennai (OMR, Velachery, Adyar, Anna Nagar, T. Nagar, Tambaram), Kolkata, Ahmedabad, Jaipur, Lucknow, Indore, Chandigarh, Coimbatore.", "default": "Bangalore" }, "propertyType": { "title": "Property type", "enum": [ "apartment", "villa", "plot", "commercial", "any" ], "type": "string", "description": "Property category. 'apartment' covers multistorey apartments / flats / builder floors — the dominant supply in Indian Tier-1 metros (Mumbai, Bangalore, Hyderabad). 'villa' covers independent houses / row houses / villas — common in Bangalore (Whitefield / Sarjapur gated communities), Gurgaon (DLF / Emaar / Sobha), and Hyderabad (Gachibowli / Tellapur). 'plot' covers residential land plots — important in Tier-2 / Tier-3 cities and outer Tier-1 (North Bangalore, Chennai OMR, outer Pune). 'commercial' covers office space, retail, shops, and showrooms — important for IT-park / SEZ / mall investment research. 'any' returns all categories.", "default": "apartment" }, "listingType": { "title": "Listing type", "enum": [ "sale", "rent" ], "type": "string", "description": "Whether to scrape sale listings or rent listings. Indian property buyers and brokers typically work one side: builders / developers / NRI investors focus on 'sale', while corporate housing teams and city-relocation services focus on 'rent'. Pricing schema differs — sale price is in INR (crores / lakhs), rent price is in INR / month.", "default": "sale" }, "bhk": { "title": "BHK filter (bedroom count)", "uniqueItems": true, "type": "array", "description": "BHK = Bedroom, Hall, Kitchen — the standard Indian property bedroom-count notation. 1BHK = studio / 1-bedroom (Mumbai compact apartments, PG-friendly). 2BHK = the volume tier for young families in Bangalore / Pune / Hyderabad (60-80% of new launches). 3BHK = mid-size family unit, the upgrade tier for IT professionals. 4BHK / 5BHK+ = premium / luxury tier (sea-facing Mumbai, golf-course Gurgaon, prime South Delhi). Leave empty to span all sizes.", "items": { "type": "string", "enum": [ "1", "2", "3", "4", "5+" ] }, "default": [] }, "budgetMinInr": { "title": "Minimum budget (INR)", "minimum": 0, "maximum": 10000000000, "type": "integer", "description": "Lower bound on listing price in Indian Rupees (INR). 1 lakh = 100,000 INR; 1 crore = 10,000,000 INR. Common buyer tiers for residential SALE: 40 lakh = entry-level Tier-2 city apartment; 80 lakh = mid Bangalore / Pune 2BHK; 1.5 crore = premium Bangalore 3BHK / mid-Mumbai 2BHK; 3 crore = luxury Mumbai / Gurgaon / South Delhi tier; 10 crore+ = ultra-prime (Worli, DLF Camellias, Lutyens Delhi). For RENT listings, scales are monthly INR: 25,000 = mid Bangalore 2BHK; 80,000 = premium Mumbai; 2 lakh+ = ultra-prime serviced apartment. Set 0 for no lower bound.", "default": 0 }, "budgetMaxInr": { "title": "Maximum budget (INR)", "minimum": 0, "maximum": 10000000000, "type": "integer", "description": "Upper bound on listing price in INR. Example: pass 10000000 (= 1 crore) to filter out luxury listings and focus on the mid-market / first-time buyer tier; pass 5000000 (= 50 lakh) for the entry-level affordable segment; pass 100000000 (= 10 crore) to slice the ultra-luxury market. For RENT, the same INR field is interpreted as INR / month. Set 0 for no upper bound.", "default": 10000000 }, "maxResults": { "title": "Max listings", "minimum": 1, "maximum": 2000, "type": "integer", "description": "Hard cap on total listings returned per run (1-2000). Each listing is one MagicBricks property record. Most recent / featured listings are returned first. Premium per-listing pricing applies — Indian property data is a high-volume residential tier matching the SG Rental Market Tracker pricing standard.", "default": 50 }, "notionConnector": { "title": "Deliver to Notion (optional)", "type": "string", "description": "Optional. Connect your Notion workspace and the listings are also written as a Notion page in the same run — the Actor never sees your Notion credentials. Authorize a Notion MCP connector in Apify Console → Settings → API & Integrations, then select it here." }, "notionParentId": { "title": "Notion parent page ID (optional)", "type": "string", "description": "Optional Notion page ID to create the page under. Blank = a private page in your workspace." } } }, "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 } } } } } } } } } } ```