Cask.news – discover and track new homebrew Mac apps

Hacker News

homebrew has over 6,000 mac apps, this huge catalog is ever growing and there's no real way to keep up with what is actually new - except when you catch that line that shows new casks when you update brew in the terminal... in case some new open source alternative drops, as we just saw with macshot essentially completely obliterating cleanshotx, you'd have no idea unless you catch it when someone posts it on hn or X. well, now there is cask.news! it automatically stays up to date with the brew.sh json and sends out instant, daily, or weekly notifications about new apps. it's also great for just browsing all the casks and finding alternative apps. I have been building on this since mid february and I finally like how it looks, its features, its auto generated reviews and ratings... and my friends told me to post it on hn so I resurrected my 16 year old account to do so :D anyway, check it out and let me know what you guys think!

Visit product View on Hacker NewsApr 28, 2026

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, apps, new · Missing: agents, macos, agent

90%90% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, 000 · Missing: https docs, excited, just released

64%64% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: apps, way · Missing: mobile apps, ios, personal

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: reviews · Missing: plus, platform, intuitive

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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