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JetClient – A Developer-Friendly Alternative to Postman and Bruno

Hacker News

JetClient – A Developer-Friendly Alternative to Postman and Bruno

Hi HN! I built JetClient, an API client plugin for JetBrains IDEs. Here are some key features: - Git Sync (File Sync) – Requests and folders are saved as separate, human-readable files. - Scripts as First-Class Citizens – In addition to pre-request/post-response scripts, you can use standalone scripts to write test suites that can reuse requests from collections. - Advanced Variables – JSON5-based variables that support arrays, objects, and expressions with built-in functions (random data, file reading, user prompts, JS evaluation, etc.). - Environment Groups – Activate multiple environments at once to test different contexts. - And much more... See key features: https://jetclient.io Compare with Postman: https://jetclient.io/docs/introduction/jetclient-vs-postman/ Compare with Bruno: https://jetclient.io/docs/introduction/jetclient-vs-bruno/ Would love your feedback!

Visit productView on Hacker NewsFeb 19, 2025
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, context · Missing: mac, agents, macos
81%81% 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
74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: friendly · Missing: plus, platform, intuitive
39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: lua, ide, io · Missing: https docs, excited, just released
38%38% 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: para · Missing: mobile apps, ios, personal
34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
14%14% 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
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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