This paper presents MyEvac, a real-time flood evacuation alert architecture that integrates citizen-submitted images and videos, analysed by Qwen2.5-VL-72B, into a three-source weighted confidence engine alongside official JPS river sensor data and Open-Meteo GloFAS v4 probabilistic forecasts. The system operationalises a distinctive integration pattern: VLM-derived structured flood variables - water depth, severity classification, visual indicators, Malay OCR-derived location, and temporal water rise rate - enter the alert confidence formula as a calibrated weighted term, controlled by an explicit two-of-three source consensus gate before geofenced alert dispatch. The system was verified through 150 automated tests and initially validated through four real-world Malaysian flood media inputs and live external API integration. Prototype deployment targets the Taman Sri Muda flood zone in Shah Alam, Selangor, Malaysia.