Craigslist Housing MCP Server — Rental Search for AI Agents

Search Craigslist housing listings across US cities. Extract price, bedrooms, location, posted date, and contact info.

🧠 MCP Server — AI Agent Ready

This actor is a Model Context Protocol (MCP) server — AI assistants can call it directly:

{
  "searchQuery": "2 bedroom apartment",
  "maxResults": 20,
  "city": "newyork"
}

Returns structured rental data: price, bedrooms, square footage, location, posted date, contact info — perfect for rental market analysis, housing price monitoring, and property AI agents.

Features

• Multi-city search — scrape multiple cities in a single run
• Detail page extraction — visit each listing's detail page for enriched data
  • Full description text
  • All photos (array of image URLs)
  • Amenities & attributes
  • Address & neighborhood
  • Post ID & posted date
  • Rent period (monthly/weekly/biweekly)
  • Listing type (apartment/room/house/sublet)
  • Reply URL for direct contact
  • Contact info hints (phone/email mentions from description)
• Structured housing data — beds, baths, sqft parsed from both search results and detail pages
• Studio listings — correctly handles "0BR" studios
• Anti-detection — PlaywrightCrawler with realistic delays
• Configurable — toggle detail extraction, set delays, limit results

Input

Field	Type	Default	Description
locations	string[]	["San Francisco, CA"]	Cities to scrape
maxResults	number	0	Max listings (0 = no limit)
fetchDetails	boolean	true	Visit detail pages for enriched data
detailDelaySecs	number	2	Delay between detail page visits

Example: Basic search

{
  "locations": ["San Francisco, CA"],
  "maxResults": 20
}

Example: Multi-city with detail extraction

{
  "locations": ["San Francisco, CA", "New York, NY", "Los Angeles, CA"],
  "maxResults": 50,
  "fetchDetails": true,
  "detailDelaySecs": 3
}

Output

Each listing includes:

Field	Source	Example
title	Search	"Bright 2 Bedroom Apartment"
price	Search / Detail	"$2,455"
beds	Search / Detail	"2"
baths	Search / Detail	"1"
sqft	Search / Detail	"729"
neighborhood	Search / Detail	"Mission District"
link	Search	"https://..."
thumbnail	Search	image URL
address	Detail	"123 Main St, San Francisco"
post_id	Detail	"7947327024"
posted	Detail	"2026-07-15"
photos	Detail	["url1", "url2", ...]
attributes	Detail	["hardwood", "laundry", ...]
description	Detail	"Full description text..."
listing_type	Detail	"apartment"
rent_period	Detail	"monthly"
housing_info	Detail	"2BR / 1Ba 729ft2"
reply_url	Detail	"https://.../reply/..."
contact_info	Detail	["Call: show contact info"]
contact_websites	Detail	["https://example.com"]
has_contact	Detail	true
location	Input	"San Francisco, CA"
scraped_at	System	ISO timestamp

Supported cities

San Francisco, New York, Los Angeles, Seattle, Chicago, Austin, Denver, Miami, Houston, Phoenix, Philadelphia, San Antonio, San Diego, Dallas, Atlanta, Portland, Nashville, Las Vegas.

Use Cases

• Rental market research — track prices and availability across cities
• Lead generation — find properties matching specific criteria for clients
• Price monitoring — run weekly to detect market trends
• Data pipeline — feed structured housing data into analytics or ML models
• Competitive analysis — monitor rental supply in target neighborhoods

Performance

• ~1-2 seconds per search page load
• ~3-5 seconds per detail page visit (network + delays)
• 4 GB RAM allocation (PlaywrightCrawler)
• Supports 18+ US cities via slug mapping

Limitations

• Craigslist does not support pagination URLs — results are dynamically loaded via scroll
• Listings may expire between search and detail fetch — handled gracefully with warnings
• Some listings lack detailed specs (no sqft, no housing_info) — those fields will be null

Pricing

Pay per event — charged per listing extracted.

💬 Quick Start for AI Assistants

Copy and paste this into ChatGPT, Claude, or another AI assistant to get help using this actor:

---

You are helping me use the "Craigslist Housing Scraper" on Apify (actor ID: udJ1lSFPz264RxA17). It extracts rental listings (apartments, rooms) from craigslist.org across US cities.

Input fields:

• locations: string array, e.g. ["San Francisco, CA", "New York, NY"]
• maxResults: number, max listings to return (0 = no limit)
• fetchDetails: boolean, visit detail pages for photos, descriptions, amenities
• detailDelaySecs: number, seconds to wait between detail page visits (default: 2)

Output fields per listing: title, price, beds, baths, sqft, neighborhood, link, address, post_id, posted, photos[], attributes[], description, listing_type, rent_period, thumbnail, h1_text, housing_info, reply_url, contact_info[], contact_websites[], has_contact, location, scraped_at.

Help me with the right input, output processing, or troubleshooting.

📋 Changelog

Version	Date	Changes
0.3	2026-07-15	Fixed reply_url extraction — Craigslist uses button.reply-button with data-href attribute. Now extracts from both button data-href and legacy anchor links
0.2	2026-07-15	Added contact extraction — reply_url, contact_info (phone/email hints from description), contact_websites (URLs in listing description), has_contact flag
0.1	2026-07-15	Added AI assistant prompt block, enriched README with use cases and comparison table, updated actor title with keywords
0.0.11	2026-07-15	Fixed beds/baths extraction — parse from housing_info spec line (1BR / 1Ba 729ft2) instead of h1 title. Studio listings now report 0 beds. Decimal baths (2.5BA) supported
0.0.7	2026-07-14	Added detail page extraction — photos, descriptions, amenities, attributes, full address, listing type, rent period
0.0.6	2026-07-14	Cloud-verified extraction across multiple cities, 200 listings, 27s runtime
0.0.1	2026-07-13	Initial release — search result extraction, PlaywrightCrawler, multi-city support

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