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Why I Built an Open-Source, Zero-Cloud Period Tracker with React 19 & Capacitor

In an era where health data is increasingly commodified, tracked, and exposed in data breaches, personal data privacy isn't just a bonus feature — it's a fundamental requirement. Most period and cycle tracking apps require cloud accounts, transmit deeply intimate health telemetry to remote servers, and integrate third-party ad SDKs. When data lives on a central server, it is vulnerable to leaks,…

In an age where personal health data faces risks of exposure through breaches and corporate sales, privacy becomes an essential aspect of personal data. Many period and cycle tracking applications rely on cloud accounts, transferring sensitive health information to remote servers and integrating third-party ad SDKs. This centralization leaves user data vulnerable to leaks, corporate monetization, and legal requests.

Aiming to address these concerns, Mooneva Cycle was developed as a 100% offline-first, private, and open-source (GPL-3.0) period and cycle tracking application for web, iOS, and Android platforms.

The core architectural principle behind Mooneva Cycle is the principle of Zero Trust and Zero Cloud. This design philosophy ensures that any data residing on the user's device cannot be compromised or leaked. Unlike traditional cloud-based period trackers, Mooneva Cycle stores data exclusively on the user's device, utilizing localStorage and Secure Storage for data management.

Additionally, Mooneva Cycle employs zero analytics, ad SDKs, or crash loggers, ensuring no user information is transmitted to external sources. This approach eliminates the risk of remote breaches, as there is no centralized database that can be targeted.

The technology stack selected for Mooneva Cycle combines modern web and native development approaches to deliver a smooth, native-like experience across iOS and Android platforms. React 19 and TypeScript form the foundation of the frontend core, while Vite 6 serves as the build tool. Capacitor 8 offers a seamless bridge between web technologies and native mobile capabilities on both iOS and Android devices.

Tailwind CSS and Vanilla CSS tokens serve as the styling foundation, while i18next provides internationalization support for 12 languages, including RTL layouts.

Key technical features and design decisions include local-first encrypted backups using PBKDF2 and AES-GCM encryption algorithms, eliminating the need for external cryptographic dependencies. The app also incorporates local push-less notifications, scheduling reminders natively through @capacitor/local-notifications without relying on cloud triggers.

Discrete Mode and local PIN protection further enhance privacy by disguising the app launcher and requiring biometric or PIN authentication. Mooneva Cycle supports non-Gregorian calendars, such as the Persian (Jalaali) solar calendar, and offers full localization support with RTL layout switching.

The app addresses the challenge of deterministic predictions on sparse data by utilizing client-side algorithms that generate cycle predictions without relying on resource-intensive machine learning techniques. True air-gapped verification ensures mobile manifest configurations do not request unnecessary network privileges or background tracking services.

Furthermore, Mooneva Cycle provides cross-platform PDF generation, creating doctor-ready clinical summaries directly within mobile WebViews without exposing sensitive data to external PDF generation APIs.

As an open-source project, Mooneva Cycle is available under the GPL-3.0 license, allowing users to access, modify, and distribute the code freely. The project welcomes contributions from the community, including translations, UI improvements, cryptographic audits, and algorithm enhancements. By providing a private, secure, and user-centric solution, Mooneva Cycle aims to empower individuals to take control of their health data while promoting open-source software development and privacy-conscious technology.

Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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