# Crexi Commercial Real Estate Listings Scraper (`jungle_synthesizer/commercial-real-estate-listings-scraper`) Actor Scrape commercial real estate listings from Crexi. Filter by transaction type, property type, state, and price range. Extracts asking price, cap rate, NOI, square footage, location coordinates, brokerage, tenancy, zoning, and marketing descriptions. - **URL**: https://apify.com/jungle\_synthesizer/commercial-real-estate-listings-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Real estate, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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 ## Crexi Commercial Real Estate Listings Scraper Scrape commercial real estate listings from [Crexi](https://www.crexi.com) — the largest commercial real estate marketplace in the US. Filter by transaction type (sale, lease, or auction), property type (office, retail, industrial, multifamily, and more), state, and price range. Returns 36 fields per listing including asking price, cap rate, NOI, square footage, tenancy type, zoning, brokerage details, GPS coordinates, and full marketing descriptions. ### What You Get Each listing record contains: - **Identifiers**: `listing_id`, `listing_url` - **Property basics**: `name`, `description`, `property_types`, `subtypes`, `status` - **Financials**: `asking_price`, `price_per_sqft`, `noi`, `cap_rate`, `pro_forma_cap_rate` - **Property details**: `square_footage`, `investment_type`, `sale_condition`, `tenancy`, `zoning`, `year_built`, `lot_size_sqft`, `occupancy_pct` - **Location**: `address`, `city`, `state`, `zip`, `county`, `latitude`, `longitude` - **Brokerage**: `brokerage_name`, `has_om` (offering memorandum available) - **Media**: `thumbnail_url` - **Content**: `marketing_description` (HTML stripped), `investment_highlights` (HTML stripped) - **Metadata**: `is_in_opportunity_zone`, `activated_on`, `updated_on`, `scraped_at` ### Input | Field | Type | Default | Description | |---|---|---|---| | `maxItems` | integer | 10 | Max listings to scrape. Leave empty for all. | | `transactionType` | string | `sale` | Filter: `sale`, `lease`, or `auction`. Leave empty for all. | | `propertyTypes` | array | `["office"]` | Property type filters (e.g. `office`, `retail`, `industrial`, `multifamily`). | | `states` | array | — | US state codes to filter (e.g. `["CA", "NY", "TX"]`). Leave empty for all. | | `minAskingPrice` | integer | — | Minimum asking price in USD. | | `maxAskingPrice` | integer | — | Maximum asking price in USD. | | `includeUnpriced` | boolean | `false` | Whether to include listings without a price. | ### Example Output ```json { "listing_id": 2569056, "listing_url": "https://www.crexi.com/properties/florida-storage-pup-leesburg", "name": "StoragePup Leesburg", "description": "Self Storage | 23,745 SqFt", "asking_price": 2050000, "price_per_sqft": 86.33, "noi": 166248, "cap_rate": 8.11, "pro_forma_cap_rate": 17.22, "square_footage": 23745, "property_types": "Self Storage", "investment_type": "Value-Add", "status": "On-Market", "year_built": 1984, "occupancy_pct": 58.0, "city": "Leesburg", "state": "FL", "latitude": 28.8095, "longitude": -81.8779, "brokerage_name": "Marcus & Millichap", "has_om": true, "marketing_description": "Marcus & Millichap is pleased to offer for sale StoragePup...", "investment_highlights": "Leesburg, Florida MSA Self-Storage Offering...", "scraped_at": "2026-06-12T13:22:44.516Z" } ```` ### Scale Crexi hosts over 200,000 sale listings and 200,000 lease listings as of mid-2026. The actor paginates the search API at 50 records per page. For a full scrape of all listings, `maxItems` can be omitted to retrieve everything. ### Notes - No authentication required — all listed data is publicly accessible via the Crexi API. - Cap rate, NOI, tenancy, zoning, and marketing descriptions are fetched from the detail endpoint for every record. - Some fields may be `null` if the listing owner did not provide that information. - All HTML is stripped from `marketing_description` and `investment_highlights`. # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `maxItems` (type: `integer`): Maximum number of listings to scrape. Leave empty to scrape all. ## `transactionType` (type: `string`): Filter by transaction type: sale, lease, or auction. Leave empty for all. ## `propertyTypes` (type: `array`): Filter by property types, e.g. office, retail, industrial, multifamily. Leave empty for all. ## `states` (type: `array`): Filter by US state codes, e.g. CA, NY, TX. Leave empty for all. ## `minAskingPrice` (type: `integer`): Minimum asking price filter in USD. ## `maxAskingPrice` (type: `integer`): Maximum asking price filter in USD. ## `includeUnpriced` (type: `boolean`): Whether to include listings without a listed price. ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "transactionType": "sale", "propertyTypes": [ "office" ] } ``` # Actor output Schema ## `results` (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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "transactionType": "sale", "propertyTypes": [ "office" ], "includeUnpriced": false }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/commercial-real-estate-listings-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "transactionType": "sale", "propertyTypes": ["office"], "includeUnpriced": False, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/commercial-real-estate-listings-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "transactionType": "sale", "propertyTypes": [ "office" ], "includeUnpriced": false }' | apify call jungle_synthesizer/commercial-real-estate-listings-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/commercial-real-estate-listings-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Crexi Commercial Real Estate Listings Scraper", "description": "Scrape commercial real estate listings from Crexi. Filter by transaction type, property type, state, and price range. Extracts asking price, cap rate, NOI, square footage, location coordinates, brokerage, tenancy, zoning, and marketing descriptions.", "version": "0.1", "x-build-id": "PqXYyzXOJao17JBVG" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~commercial-real-estate-listings-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-commercial-real-estate-listings-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/jungle_synthesizer~commercial-real-estate-listings-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-commercial-real-estate-listings-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/jungle_synthesizer~commercial-real-estate-listings-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-commercial-real-estate-listings-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": [ "maxItems" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of listings to scrape. Leave empty to scrape all." }, "transactionType": { "title": "Transaction Type", "type": "string", "description": "Filter by transaction type: sale, lease, or auction. Leave empty for all." }, "propertyTypes": { "title": "Property Types", "type": "array", "description": "Filter by property types, e.g. office, retail, industrial, multifamily. Leave empty for all.", "items": { "type": "string" } }, "states": { "title": "States", "type": "array", "description": "Filter by US state codes, e.g. CA, NY, TX. Leave empty for all.", "items": { "type": "string" } }, "minAskingPrice": { "title": "Min Asking Price (USD)", "type": "integer", "description": "Minimum asking price filter in USD." }, "maxAskingPrice": { "title": "Max Asking Price (USD)", "type": "integer", "description": "Maximum asking price filter in USD." }, "includeUnpriced": { "title": "Include Unpriced Listings", "type": "boolean", "description": "Whether to include listings without a listed price." } } }, "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 } } } } } } } } } } ```