Nowdex – AI agent usage on your iPhone

Hacker News

Hi HN, I've been using Claude Code, Codex and Cursor quite a bit lately, and I found myself checking their usage limits all the time. Most of the tools I found for this live on the desktop or in the menu bar. What I really wanted was to pull out my phone and see how much I had left, especially when I'm away from my computer. I ended up building Nowdex for this. The main thing is the iPhone widget. It shows your current usage and reset time directly on the Home Screen or Lock Screen. Right now it supports Claude, Codex, Cursor, Grok, Kimi and GLM. There is no account thing. The app doesn't send your usage data to my server, all data live on your device, and sync between your Apple devices is done through iCloud. > One note if you try the Mac app: the version currently on the App Store has a bug that prevents connecting accounts. It's fixed in the next version, which is currently waiting for App Review. Apple review takes toooo long :) I'm also working on an Apple Watch version since this feels like exactly the kind of information I'd rather glance at than open an app for. It's a paid app, but only if you need to track a lot providers. No subscription. Happy to answer any questions.

Visit product View on Hacker NewsSep 14, 2026

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

98%98% 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.

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

88%88% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

46%46% predicted probability of success on TrustMRR, 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

28%28% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

15%15% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

Correct prediction on native model

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