Criblist turns SF apartment hunting into a swipeable deck. Set your budget, neighborhoods, and must-haves, then browse live rentals from Craigslist and local property managers. Context.dev powers the extraction and source data. Keep the good ones.
Hey Product Hunt 👋
Apartment hunting in San Francisco has a painfully specific loop:
Open Craigslist
Open five property manager websites
See the same listing twice
Lose the good one
Start another spreadsheet
Repeat
So we built Criblist.
Tell it your budget, bedroom count, preferred neighborhoods, and the things you refuse to compromise on. Criblist searches live inventory across Craigslist, Brick + Timber, RentSFNow, Mosser, and J. Wavro, then gives you one clean, personalized deck.
Pass. Keep. Open the original listing. Move on.
We built Criblist on top of Context.dev:
The HTML API fetches live listing pages
The Extract API turns messy rental websites into structured inventory
The Brand API keeps every source recognizable
We also made a deliberate choice not to pad the results. If nothing genuinely matches what you asked for, Criblist tells you instead of showing you a bunch of irrelevant apartments.
It’s completely free, requires no login, and is fully open source.
If you’re looking for an apartment in SF right now, reply with:
Budget / bedrooms / two neighborhoods / one dealbreaker
We’ll run your search and share the best match Criblist finds 👀
the swipe-and-keep format is a great fit for this, apartment hunting really is just a matching problem dressed up as a spreadsheet. one thing I'd want to know before trusting it: does Criblist re-check that a listing is still live before showing it to me, or is there a chance I keep something that already got rented out an hour earlier? SF listings move fast
How do you plan to handle sourcing and data consistency from Craigslist, given their historical issues with scraper bots and varying listing quality?
Nice work Yahia. I will try to integrate Context.dev for Commercial Real Estate again.
As a student, the struggle is real. How often do you find listings that aren't duplicated across multiple sites?
It would be super helpful to see a map view alongside the swipe deck so I can visualize where each listing sits relative to my target neighborhoods and commute. Maybe a small toggle in the corner to switch between card stack and map mode. Would make narrowing down the geography way easier without losing the quick-browse feel.
A commute-time filter would be huge. Plug in where you work and it shows you listings under your max door-to-door time on Muni or BART, not just the rent number. Right now I still have to mentally cross-check every place against how long it'll actually take me to get to the office.
About SF Apartment Finder on Product Hunt
“Tinder for live SF rentals from across the web”
SF Apartment Finder launched on Product Hunt on July 26th, 2026 and earned 169 upvotes and 9 comments, earning #3 Product of the Day. Criblist turns SF apartment hunting into a swipeable deck. Set your budget, neighborhoods, and must-haves, then browse live rentals from Craigslist and local property managers. Context.dev powers the extraction and source data. Keep the good ones.
SF Apartment Finder was featured in Design Tools (261.5k followers), API (98.4k followers), GitHub (41.3k followers) and Community (3.1k followers) on Product Hunt. Together, these topics include over 81.5k products, making this a competitive space to launch in.
Who hunted SF Apartment Finder?
SF Apartment Finder was hunted by Yahia Bakour. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how SF Apartment Finder stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Yahia Bakour