JSON Dive – A better online JSON viewer

Hacker News

We've all been there: you have some JSON data you need to make sense of, so you Google "json formatter" and end up at a site ridden with ads. I used to look at at lot of JSON (mostly log data) for $oldjob, so I set out to build something better. I know there are a lot of tools in this space, but I've put a lot of love into JSON Dive: things like Vim keyboard shortcuts to navigate, dark mode, timestamp/image previews, and multi-file-format-support (XML-in-JSON was a format I dealt with in the context of LLMs/tool calls). I've also made an effort to ensure it can handle large files, since no one wants their tool to break down in that scenario. The entire thing is local-first and never sends your data anywhere. I'm hoping to support the development of JSON Dive and stay ad-free in two ways: 1. Premium features (in development; mostly around collaboration). Note that everything that's free right now will remain free; these would be additive. 2. Licensing. JSON Dive is built as a React component that you can embed in your application. My vision is that instead of copy/pasting into JSON Dive, whatever tool I was using would already have JSON Dive in it :) I'd love feedback. More importantly, I'd love it if JSON Dive became a tool that improved your life as a developer!

Visit product View on Hacker NewsSep 25, 2025

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

75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: 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.

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

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

13%13% 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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