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Voiden – a free, offline, Git-native API Client

Hacker News

Voiden – a free, offline, Git-native API Client

Hey HN! Aldin here, a helping hand to Voiden ( https://voiden.md ) Voiden is a free, offline, Git-native API client. Your API definitions, docs, and tests all live together. It came out of years of frustration: cloud sync lock-in, paywalled basics, bloated UIs, and lag on even simple requests. So the team built the opposite: an offline tool with no login, no telemetry, no lock-in. Just markdown and hotkeys. It behaves like code: local files, git branches, no cloud nonsense. Terminal is built-in, so you can commit, diff, and push changes right from the app. Docs stay close to your requests, so that API spec and what the API actually does never drift apart. No more scattered Postman, docs, and test files everywhere. A single source of truth. A minimalist GET request looks something like this: GET https://dummyjson.com/posts Just hit /endpoint, paste the URL, and run it with Cmd/Ctrl + Enter. Not OSS (yet), but 100% local and free. Optional plugins will be coming down the line, but the core stays free. We'd love feedback from folks tired of overcomplicated and bloated API tooling.

Visit product View on Hacker NewsMay 28, 2025

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Launch Intel predictions

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

89%89% 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 NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

50%50% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

41%41% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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 · Missing: arr, mrr, revenue

15%15% 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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