Breast cancer is the cancer with the highest incidence and mortality among women worldwide. In Indonesia, delayed diagnosis remains largely associated with low awareness of symptoms and limited access to early screening services at primary healthcare facilities. This study aims to design, develop, and evaluate the functionality of MAMAI-Check v1.8.5, an integrated breast cancer surveillance system based on a Progressive Web App (PWA) that combines self-education, symptom assessment, and risk screening with real-time data reporting for primary healthcare workers. The study employed a Research and Development (R&D) approach through four software engineering stages: requirements and system architecture analysis, user interface and user experience (UI/UX) design, system development, and black-box functionality testing. The application was developed using React 18 and TypeScript, with Tailwind CSS for layout design, and integrated with Firebase Firestore and Google Sheets for real-time data synchronization, supported by a service worker for offline access. The development resulted in eight integrated modules, including a home page, identity form and body mass index (BMI) calculator, breast self-examination (SADARI) and clinical breast examination (SADANIS) education center, interactive symptom checklist, self-administered risk screening questionnaire, automated recommendation and history module, FAQ, and a healthcare worker dashboard for population surveillance monitoring. Black-box testing demonstrated that all modules, input validation, risk assessment algorithms, and data synchronization operated according to the technical specifications and screening criteria established by the Indonesian Ministry of Health. These findings indicate that a lightweight PWA that can be installed without an application store can expand breast health awareness education and structured risk triage to primary healthcare facilities without replacing clinical diagnosis, making it a potential digital complement to early detection programs in resource-limited settings.