Cumbersome – iOS/macOS API client for OpenAI, Anthropic, Z.ai

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It's called Cumbersome because you have to wrangle API keys (versus just using ChatGPT directly). So, I think of it like driving with a manual transmission, and all the benefits you get there, versus everything-on-auto. Not always easy, but often better (well, for some). This means you can bypass the monthly subscriptions for AI providers and just pay directly. This can work out to be a lot cheaper (or not!) depending on your use. Actually I made this because I much prefer the API sandboxes/playgrounds of the AI providers, versus their consumer apps. You can edit context, delete bad context, rewrite AI messages. So you can do all that in Cumbersome, and a bunch of other things too. I also threw in some features like Face/Off Mode where you can get 3 responses at once, and the AI picks the best. (Cursor recently added an ensemble feature like this.) This can be really spendy, but it's worth it for high-value AI sessions. (And it's probably never something that the all-you-can-eat consumer plans will offer as they are incentivized to cheap out.)

Visit product View on Hacker NewsDec 29, 2025

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

96%96% 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: ios · Missing: supports, reddit linkedin, podcasting

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

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

60%60% 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

37%37% 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

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: subscription · 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 · Strong signals: chat · Missing: web3, crypto, cryptocurrency

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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