Craigslist Scraper — Listings, Prices & Locations

Scrape Craigslist listings from any US city, category, and search query. Get title, price, images, location, post ID, and listing URL — plus optional description, posted datetime, and structured attributes (car specs, condition, odometer, etc.) from detail pages. This Craigslist scraper targets the JSON-LD ItemList block embedded by Craigslist itself — structural schema.org data, not CSS class names — making it immune to layout redesigns. No proxy required. Pay per result at $1.39 per 1,000 listings.

Not affiliated with or endorsed by Craigslist.

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What you get

Field	Source	Notes
post_id	DOM link	10-digit Craigslist post ID
title	JSON-LD	Listing title
price	JSON-LD	Numeric float; null for free/contact items
price_currency	JSON-LD	"USD"
city	JSON-LD	City name (e.g. "San Francisco")
state	JSON-LD	State abbreviation (e.g. "CA")
neighborhood	Detail page	Sub-city neighborhood; null if not set
latitude / longitude	JSON-LD + detail	Precise coords from detail page when fetchDetails=true
url	DOM link	Full listing URL
category	URL	Category abbreviation (e.g. "bik", "cto")
area_abbrev	URL	Metro sub-area (e.g. "sby", "sfc")
posted_datetime	Detail page	ISO-8601 UTC; requires fetchDetails=true
image_urls	JSON-LD	Array of full-size CDN image URLs
description	Detail page	Plain-text body; requires fetchDetails=true
attributes	Detail page	Dict of label→value (condition, make, cylinders, etc.)
parse_confidence	Computed	0.0–1.0 data quality score
warnings	Computed	List of parse-issue codes
scraped_at	Computed	ISO-8601 UTC timestamp

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Common city slugs

City	Slug
San Francisco Bay Area	sfbay
New York	newyork
Los Angeles	losangeles
Chicago	chicago
Seattle	seattle
Austin	austin
Boston	boston
Denver	denver

Full list: https://www.craigslist.org/about/sites

Common category codes

Category	Code
For sale — all	sss
Bicycles	bik
Cars & trucks by owner	cto
Electronics	ele
Furniture	fua
Apartments	apa
Jobs	jjj
Clothing	clt

Full list: https://www.craigslist.org/about/help/abbreviations

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Example input

{
  "city": "sfbay",
  "query": "honda civic",
  "category": "cto",
  "maxResults": 50,
  "fetchDetails": true
}

Example output record

{
  "post_id": "7938685561",
  "title": "2018 Honda Civic EX",
  "price": 18500.0,
  "price_currency": "USD",
  "city": "San Jose",
  "state": "CA",
  "neighborhood": "South Bay",
  "latitude": 37.3403,
  "longitude": -121.9701,
  "url": "https://sfbay.craigslist.org/sby/cto/d/san-jose-2018-honda-civic-ex/7938685561.html",
  "category": "cto",
  "area_abbrev": "sby",
  "posted_datetime": "2026-06-04T10:51:23+00:00",
  "image_urls": ["https://images.craigslist.org/00h0h_ABC_600x450.jpg"],
  "description": "Clean title, low miles, well maintained...",
  "attributes": {
    "condition": "excellent",
    "cylinders": "4 cylinders",
    "drive": "fwd",
    "fuel": "gas",
    "odometer": "45,000",
    "title status": "clean",
    "transmission": "automatic"
  },
  "parse_confidence": 1.0,
  "warnings": [],
  "scraped_at": "2026-06-04T12:00:00+00:00"
}

---

How it works

1. One HTTP request fetches the Craigslist search page for your city/category/query.
2. JSON-LD parsing (structural, not CSS): Craigslist embeds all results as a schema.org ItemList in the page <head>. Up to ~350 results per query.
3. DOM link extraction: listing URLs (with post_id, category, area_abbrev) are extracted from <a> tags in the body and matched to JSON-LD items by title slug.
4. Detail page (optional): each listing's page is fetched for posted_datetime, description, and structured attributes.

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Pricing

Pay-per-result: $0.00139 per listing ($1.39 / 1,000 listings).

With fetchDetails=false (default): ~1 request/run → very fast, very cheap.
With fetchDetails=true: 1 + N requests (one per listing) → richer data, proportionally more compute.

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Use cases for Craigslist data

• Price research — benchmark used car, electronics, or furniture prices across cities
• Real estate leads — monitor for-rent and for-sale listings in target neighborhoods
• Resale arbitrage — find underpriced items listed by private sellers
• Job market intelligence — pull job listings from the jjj category across metros
• Academic research — analyze classifieds data for economics or sociology studies
• Competitor monitoring — track similar items listed by other sellers in your category

Frequently asked questions

Do I need a proxy? No. Craigslist search pages are server-side rendered and respond 200 from datacenter IPs. No proxy configuration is needed.

How many results per search? Craigslist includes all matching results in one JSON-LD block — typically up to ~350 items per query. For more coverage, run multiple narrowed queries.

How do I get descriptions and car specs? Set fetchDetails: true. This fetches each listing's detail page to extract description, posted_datetime, neighborhood, precise latitude/longitude, and structured attributes (condition, make, cylinders, etc.). This multiplies request count by N listings.

What is fetchDetails=false good for? Fast, cheap bulk listing collection — title, price, images, location, and URL from a single search-page request. Good for price monitoring and deduplication.

What does parse_confidence mean? 0.0–1.0 data quality score. 1.0 = all critical fields extracted. Below 0.7 = Craigslist may have changed its JSON-LD structure; check warnings for affected fields.

Can I scrape multiple cities? Yes — run the actor multiple times with different city slugs, or use Apify's batch run API to fan out across cities in parallel.

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Limitations

• Results per search: up to ~350 (Craigslist's JSON-LD includes all results in one page).
• posted_datetime, description, attributes require fetchDetails=true.
• neighborhood is only available on listings where the poster set it.
• Craigslist does not expose full posted_datetime on search pages.

Integrations

Built for market researchers and resellers tracking US local listings, pricing trends, and inventory by city and category — the JSON/dataset output drops into the tools you already run, no glue code:

• n8n / Make / Zapier — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: n8n, Make, Zapier.
• Webhooks — fire your own endpoint the moment a run finishes, to push results straight into your pipeline (docs).
• MCP server — expose this actor as a tool to Claude, Cursor, or any MCP client so an AI agent can pull this data mid-conversation (guide).
• API & SDKs — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs.

See all Apify integrations.

More scrapers from our toolkit

Building a data pipeline? These actors pair well with this one — each runs on your own Apify account with the same pay-per-result pricing, no subscription:

• Doordash Scraper
• Ebay Scraper
• Etsy Listings
• Facebook Marketplace Scraper
• Grailed Listings
• Kleinanzeigen Listings Scraper

Chain any of them together from the Integrations tab (the Run succeeded trigger) to build a multi-step workflow — one actor's output feeds the next.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.