MyClimateCoach

• 

  Documentation Part 1

• 

  Documentation Part 2

We were inspired by the feeling that climate change is too big for one person to impact. While data is abundant, few tools help people understand what they can actually do. Our goal was to make climate education personal, practical, and empowering — turning awareness into daily action.

This was our first real project as a team, and it taught us how to integrate APIs, design user flows, and use AI meaningfully. We built MyClimateCoach in Lovable, combining: Google Gemini AI for personalized eco-advice and explanations. Open-Meteo API for live weather and air-quality data. Supabase for storing eco-scores and leaderboards.

The app suggests climate-positive actions based on real-time data and explains why they matter, making learning interactive and relevant. Users can also earn rewards for completed activities.

We faced challenges integrating APIs and crafting effective prompts, but we learned fast and exceeded our expectations.

Next, we plan to add local sustainability events where verified users can gather and take action together — making the world safer, one location at a time.

Built With

• authentication
• flash
• google-gemini-2.5-pro
• json
• jwt-authentication
• lovable
• open-meteo-api
• openstreetmap-nominatim-api
• postgresql
• react
• recharts
• shadcn
• supabase
• tailwind-css
• typescript
• vite