Mounjy – a private GLP-1 tracker for shots, weight, side effect

Hacker News

I built Mounjy for people using GLP-1 medications like Mounjaro, Zepbound, Ozempic, and Wegovy. I wanted a more private, focused tracker for logging shots, weight, side effects, progress photos, reminders, and Apple Health data without needing another account. Would love feedback, especially on the product direction, onboarding, and what feels missing for long-term GLP-1 tracking. For anyone here who wants to try it, you can redeem 6 months free with code MOUNJYFREE in the app.

Visit product View on Hacker NewsApr 21, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: apple, using, code · Missing: mac, agents, macos

83%83% 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.

TrustMRRFits verified-revenue profile · Strong signals: month · Missing: mobile apps, ios, personal

59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

26%26% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

25%25% 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

21%21% 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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