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MinitQ

MinitQ is an interactive quiz game that combines trivia knowledge with blockchain rewards. Players answer themed questions to earn MNTQ tokens for correct answers.

Technical Overview

MinitQ is a full-stack web application that combines traditional quiz gameplay with blockchain rewards. Built using FastAPI for the backend and vanilla JavaScript for the frontend, it demonstrates the integration of Web3 functionality using the Coinbase Developer Platform (CDP).

Core Features:

  1. Quiz Mechanics:
    Multiple-choice questions
    Score tracking
    Interactive web interface
    Persistent leaderboard system

  2. Web3 Integration:
    Custom ERC20 token (MNTQ) for rewards
    Smart contract integration for token minting
    Automated reward distribution (10 MNTQ tokens per correct answer)
    Token contract deployed at 0xc90278252098de206ae85A4cb879123d50a05456 on base sepolia

  3. Architecture:
    Frontend: HTML5, CSS3, and vanilla JavaScript
    Backend: FastAPI (Python)
    Database: Replit DB for leaderboard storage
    Blockchain: CDP SDK for Web3 interactions
    AI Agent: Custom TokenAgent for reward distribution

  4. User Flow:
    User input their Web3 wallet address
    Answers 5 themed questions
    Receives MNTQ tokens based on performance
    Views their position on the global leaderboard
    Option to play again

  5. Technical Features:
    Asynchronous API endpoints
    Secure token minting system
    Real-time score updates
    Optimized smart contract interactions
    Automated reward calculations
    Persistent leaderboard rankings
    Clean separation of concerns (MVC pattern)

The project serves as an example of how traditional web applications can be enhanced with Web3 and AI Agent functionalities, providing both entertainment and rewards for user participation. The modular architecture allows for easy expansion of both quiz content and reward mechanisms.

Future Works

  1. Quiz theme and questions generations using AI Agents
  2. Wallet Connection and Management features in the frontend
  3. Enhance UI/UX
  4. Conduct live events using AI Agents

Languages

Python60.8%JavaScript21.9%CSS8.0%HTML6.8%Roff2.1%Nix0.4%

Contributors

Created February 9, 2025
Updated February 9, 2025
sanandmv7/minitq | GitHunt