Open-source user authentication for Next.js

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Hi all! With my friend Zai, we are building Stack ( https://github.com/stackframe-projects/stack ), a set of open-source libraries to help make projects production-ready. We want to close the gap between "prototype" and "launchable". Our first module is user authentication. This is a messy space where you can roughly divide the current incumbents into at least one of three camps: - Proprietary; with vendor lock-in and MAU-based pricing when you scale - Basic feature set; missing things that would be useful especially in the first week, such as token-based auth, a user dashboard with analytics, frontend components, and well-supported credential authentication - Bad DX; difficult setup and lots of initial configuration even for basic features (such as OAuth) If you'd like to validate an idea you built on a Thursday evening, there are no great solutions available. Enter Stack! An open-source and self-hostable authentication server and library. Besides basic auth features, I think there are three ways in which we do really well: - Frontend integration: We provide React/Next.js components and hooks that are highly customizable. They adapt to your design system; so if you use eg. MUI, they will use MUI components, too. - Dashboard and monitoring: We have a dashboard where you can list, visualize, and manage your users. You can also use our components to build your own. - Modularity: Stack itself is an OpenID identity provider and has a RESTful API. If you're using a different OAuth client library, you can still use our server. Stack itself is open-source licensed under MIT and AGPL. We provide a paid hosted service that we call Stackframe [1]. It has very simple pricing, with unlimited MAU on every paid plan. There are no differences between the hosted and the OS version. Check out our docs [2], or if you'd like to be part of this, join our Discord [3]. Cheers! [1] https://stackframe.co [2] https://docs.stackframe.co [3] https://discord.gg/pD4nyYyKrb

Visit product View on Hacker NewsMar 20, 2024

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

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

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Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

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

44%44% 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

29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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