Mi

Mintlify Ignored This Feature Request for 6 Months. Here's My Solution

Hacker News

Mintlify Ignored This Feature Request for 6 Months. Here's My Solution

Mintlify users have been begging for pre-filled API playground fields for months. The GitHub discussion has people literally saying "I just lost two hours of my day banging my head against this issue." ( https://github.com/orgs/mintlify/discussions/759 ) The problem? When you click "Try it" in Mintlify's playground, every field is empty, even though your OpenAPI spec has perfectly good example values sitting right there. Your developers have to manually type or copy-paste data just to test a single endpoint. It's 2025. This is insane. So we built madrasly. Run npx madrasly your-spec.json output-dir and you get a fully interactive API playground with all fields pre-populated from your OpenAPI examples. Path parameters, query params, request bodies—everything just works. One command, zero configuration, and your developers can actually test your API without wanting to throw their laptop. Check out the live demo or grab it from GitHub. If Mintlify won't fix it, we will. Feel free to star us on GitHub! We also offer free hosting on our website (no paid tiers available). madrasly.com.

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Actual performance

1points
Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting
79%79% 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: user, single, open · Missing: mac, agents, macos
75%75% 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
56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: month, users, para · Missing: mobile apps, ios, personal
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: host, users · Missing: plus, platform, intuitive
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, 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.

Incorrect prediction on native model

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