# Realtor Leads Real Estate Agent Scraper (`olympus/realtor-leads-real-estate-agent-scraper`) Actor $1/1k leads | Pull verified real estate agent profiles, emails, phones, ratings, bios, social links, brokerage details from Realtor.com in minutes. - **URL**: https://apify.com/olympus/realtor-leads-real-estate-agent-scraper.md - **Developed by:** [Olympus](https://apify.com/olympus) (community) - **Categories:** Real estate, Lead generation, Automation - **Stats:** 2 total users, 1 monthly users, 33.3% runs succeeded, 1 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $2.00 / 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 ## Realtor.com Agent Scraper Stop searching manually. Pull verified real estate agent profiles, emails, phones, ratings, bios, social links, brokerage details — from [Realtor.com](https://www.realtor.com) in minutes. Any city. Any zip. Any state. --- ### Why It Slaps ⚡ Rips full agent profiles straight from Realtor.com — no manual digging required 📬 Surfaces emails that aren't even publicly listed on the site 🔁 Picks up exactly where it stopped if interrupted, your credits don't go to waste 🎯 Filters by rating, agent type, and location so you only get what you actually need --- ### Fire It Up in 5 Steps **Step 1 — Tell it where to look** Drop your locations into the `locations` array. Check below for the accepted formats. **Step 2 — Get picky (optional)** Only want 4-star agents? Set `minRating`. Only chasing buyer-side reps? Flip `agentType`. You're in control. **Step 3 — Set a ceiling** `limitPerLocation` keeps things manageable. Start lean, preview your data, then open the floodgates. **Step 4 — Let it run, then grab your data** Sit back. When it's done, pull your results as JSON, CSV etc. **Step 5 — Interrupted? No stress** Re-run with the same settings and it continues from exactly where it stopped. Only switching up locations, rating, or agent type resets progress. --- ### What Goes In | Field | Default | Description | |---|---|---| | `locations` | — | One or more locations to search. Enter any mix of city + state (Chicago, IL), zip code (60601). Stack as many as you want. | | `limitPerLocation` | `1000` | Max agents to collect per location. | | `minRating` | `0` | Minimum star rating (1–5). Set to `0` for no filter. | | `agentType` | `both` | Filter by specialisation: `buyer`, `seller`, or `both`. | #### Quick Example ```json { "locations": ["Chicago, IL", "Houston, TX"], "limitPerLocation": 500, "minRating": "3", "agentType": "both" } ```` *** ### 📍 Location Format — Get It Right First Time Locations must be entered as **City, ST** the city name, a comma, then the 2-letter state abbreviation. Zip codes work too. **✅ What Works** | Input | Type | |---|---| | `Austin, TX` | City + state | | `Los Angeles, CA` | City + state | | `New York, NY` | City + state | | `Miami, FL` | City + state | | `Chicago, IL` | City + state | | `90210` | Zip code | | `10001` | Zip code | **❌ What Breaks It** | Input | Why It Fails | |---|---| | `Austin, Texas` | Full state name — use `TX`, not `Texas` | | `Austin TX` | Missing comma between city and state | | `United States` | Country names aren't supported | | `California` | State-only isn't supported — must include a city | **📝 Good to Know** - Stack as many locations as you want — each is scraped independently up to your `limitPerLocation` - State abbreviations are case-insensitive, but uppercase is preferred — `TX` over `tx` - Multi-word cities work perfectly — `Los Angeles, CA`, `San Francisco, CA`, `New York, NY` *** ### What Comes Out Every agent. Every detail. One record each. | Field | Description | |---|---| | `fullName` | Agent's full name | | `emails` | Extracted email addresses | | `phones` | Phone numbers (personal and office) | | `websiteUrl` | Agent's personal website | | `bio` | Agent biography | | `title` | Experience label (e.g. "12 years 4 months of experience") | | `intentType` | Listed intent types (e.g. BUYER, SELLER) | | `officeName` | Brokerage or office name | | `officeAddress` | Office address | | `licenseNo` | Real estate license number | | `licenseState` | State the license is issued in | | `city` / `state` / `zip` | Agent location | | `country` | Country (US) | | `languages` | Languages spoken | | `specialties` | Areas of specialisation | | `servedAreas` | Areas the agent covers | | `reviewScore` | Average star rating | | `reviewCount` | Number of reviews | | `recommendations` | Number of client recommendations | | `recentlySold` | Recently sold properties count | | `activeListings` | Active for-sale listings count | | `priceMin` / `priceMax` | Annual combined listing price range | | `servicesBuyer` | Buyer services offered | | `servicesSeller` | Seller services offered | | `photoUrl` | Agent headshot URL | | `facebook` | Facebook profile link | | `twitter` | Twitter / X profile link | | `linkedin` | LinkedIn profile link | | `instagram` | Instagram profile link | | `youtube` | YouTube channel link | | `isPaid` | Whether the agent has a paid listing | | `isRealtor` | Whether the agent is a verified REALTOR® | *** #### ◆ Scraping the Profiles — $2/1k leads Names, bios, ratings, office info, social handles, emails, phone numbers, all of it, pulled clean. *** ### Support Open a ticket on the **Issues** tab or contact support at **olympusdev001@gmail.com**. # Actor input Schema ## `locations` (type: `array`): Enter any mix of city + state (Chicago, IL), zip code (60601). Add as many as you need. ## `limitPerLocation` (type: `integer`): Maximum number of agents to collect per location. ## `minRating` (type: `array`): Filter agents by minimum star rating on Realtor.com (1–5 stars). Set to 0 to return all agents regardless of rating. ## `agentType` (type: `string`): Filter agents by specialisation. Buyer, seller, or both. ## Actor input object example ```json { "locations": [ "Chicago, IL" ], "limitPerLocation": 1000, "agentType": "both" } ``` # Actor output Schema ## `leads` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "locations": [ "Chicago, IL" ] }; // Run the Actor and wait for it to finish const run = await client.actor("olympus/realtor-leads-real-estate-agent-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "locations": ["Chicago, IL"] } # Run the Actor and wait for it to finish run = client.actor("olympus/realtor-leads-real-estate-agent-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 '{ "locations": [ "Chicago, IL" ] }' | apify call olympus/realtor-leads-real-estate-agent-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=olympus/realtor-leads-real-estate-agent-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Realtor Leads Real Estate Agent Scraper", "description": "$1/1k leads | Pull verified real estate agent profiles, emails, phones, ratings, bios, social links, brokerage details from Realtor.com in minutes.", "version": "0.1", "x-build-id": "Qh9ibCeyoVJ8GbyLv" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/olympus~realtor-leads-real-estate-agent-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-olympus-realtor-leads-real-estate-agent-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/olympus~realtor-leads-real-estate-agent-scraper/runs": { "post": { "operationId": "runs-sync-olympus-realtor-leads-real-estate-agent-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/olympus~realtor-leads-real-estate-agent-scraper/run-sync": { "post": { "operationId": "run-sync-olympus-realtor-leads-real-estate-agent-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": [ "locations" ], "properties": { "locations": { "title": "Locations e.g Chicago, IL", "type": "array", "description": "Enter any mix of city + state (Chicago, IL), zip code (60601). Add as many as you need.", "default": [], "items": { "type": "string" } }, "limitPerLocation": { "title": "Limit per location", "minimum": 100, "maximum": 50000, "type": "integer", "description": "Maximum number of agents to collect per location.", "default": 1000 }, "minRating": { "title": "Minimum star rating", "type": "array", "description": "Filter agents by minimum star rating on Realtor.com (1–5 stars). Set to 0 to return all agents regardless of rating.", "items": { "type": "string", "enum": [ "0", "1", "2", "3", "4", "5" ], "enumTitles": [ "No filter", "1+", "2+", "3+", "4+", "5" ] } }, "agentType": { "title": "Agent type", "enum": [ "both", "buyer", "seller" ], "type": "string", "description": "Filter agents by specialisation. Buyer, seller, or both.", "default": "both" } } }, "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 } } } } } } } } } } ```