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OpenAPI Zapier Generator

Hacker News

OpenAPI Zapier Generator

Hey HN! We've developed a way to turn API specifications, like OpenAPI 3.0, into Zapier Triggers and Actions for you to automate parts of an app, with the added benefit of SDK generators. Documenting endpoints sucks. What sucks more is a clunky interface to let nontechnical use your app or outdated/nonexistent SDKs for technical people to set and forget. This project originated from my cofounder and I having to make Zapier.com and Make.com apps frequently while not getting what we wanted out of https://openapi-generator.tech/docs/generators/zapier/ . Our installation/setup is straightforward with a dashboard and Make/Zapier keys. Create an API spec by using our request scanning extension or the supported docker plugin. If you have an API spec ready to go, plug it in on the uploads page. Next, you hit the create Zapier or Make plugin, and it generates then uploads the code to your developer dashboard on either respected platform once you have parametrized the API paths. We're starting off with API-key based auth for Make and Zapier. It's free and appreciate any feedback as we are ironing out bugs. We're excited to hear what you all think and please try it out! Portway.ai

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Actual performance

17points
1comments
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: apps, dock, using · Missing: mac, agents, macos
73%73% 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: para · Missing: supports, reddit linkedin, podcasting
63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: apps, way, para · Missing: mobile apps, ios, personal
57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, exist, io · Missing: https docs, just released, lua
53%53% 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: platform, interface · Missing: plus, intuitive, reviews
37%37% 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
22%22% 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.

Correct prediction on native model

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