This paper presents a comprehensive framework for integrating BCI systems with mobile devices to enhance accessibility and practical applications. The proposed framework encompasses four core elements: data capture, preprocessing and feature extraction, model configuration, and integration and development. EEG signals are captured and preprocessed using signal filtering and the Common Spatial Pattern method, followed by classification with a Support Vector Machine (SVM) model. The integration phase leverages modern technologies such as Supabase for data storage, Heroku for hosting the API, and Flutter for mobile app development. The framework’s efficacy is demonstrated through a case study, achieving high classification accuracy and robust performance metrics. This research aims to bridge the gap between BCI technology and mobile platforms, paving the way for novel applications and more intuitive user interactions with technology.