MCQ Video Generator 🎬 ✨

Transform your multiple-choice questions into engaging video presentations

📋 Overview

The MCQ Video Generator is a powerful tool designed to automatically convert CSV-formatted multiple-choice questions into professional video presentations with synchronized audio narration. Perfect for educators, trainers, and content creators looking to enhance learning materials without the hassle of manual video editing.

✨ Features

• 🎥 Automated Video Creation - Transform CSV files of MCQs into complete videos
• 🔊 Text-to-Speech Narration - Automatic audio generation for all text elements
• 🌐 Multi-language Support - Compatible with various languages through gTTS
• 🎨 Customizable Styling - Control colors, fonts, and dimensions
• 🔄 Batch Processing - Process multiple questions in a single run

🛠️ Installation

Prerequisites

• Python 3.12 or higher
• Required font file (default: HindVadodara-Light.ttf)

Setup

1. Clone the repository

git clone https://github.com/yourusername/mcp-video-gen.git
cd mcp-video-gen

2. Install the required dependencies

pip install -e .
# or
pip install pandas pillow gtts moviepy

3. Install additional MCP dependencies

pip install mcp[cli]>=1.6.0

🚀 Usage

Basic Usage

python main.py

As an MCP Tool

This tool is designed to work within the MCP (Machine Control Protocol) framework:

from mcp.server.fastmcp import FastMCP
from main import create_mcq_video

# Create an MCP server
mcp = FastMCP("mcq_video_generator")

# Example usage
result = await create_mcq_video(
    csv_file_path="your_questions.csv",
    output_filename="my_quiz_video.mp4"
)

📊 Input Format

Your CSV file should contain columns for questions and answer options. Example format:

Question	A	B	C	D	Answer
What is 1+1?	A. 1	B. 2	C. 3	D. 4	Ans: B. 2
Capital of France?	A. London	B. Berlin	C. Paris	D. Rome	Ans: C. Paris

⚙️ Configuration Options

Parameter	Description	Default
csv_file_path	Path to input CSV file	Required
output_filename	Name for final video	"Gyan_Dariyo_final_video.mp4"
language	Language code for TTS	"en"
font_path	Path to font file	"HindVadodara-Light.ttf"
font_size	Text size on slides	70
img_width	Video width (pixels)	1920
img_height	Video height (pixels)	1080
bg_color_rgb	Background color	(0, 127, 215)
font_color_rgb	Text color	(255, 255, 255)

📋 Process Flow

graph TD
    A[Load CSV Data] --> B[Generate Images]
    B --> C[Create TTS Audio]
    C --> D[Combine into Video Clips]
    D --> E[Concatenate Final Video]
    E --> F[Output MP4 File]

🔍 Technical Details

The tool performs the following steps:

1. 📑 Reads MCQ data from a CSV file
2. 🖼️ Generates an image for each MCQ with proper text formatting
3. 🎙️ Creates audio narration using Google's Text-to-Speech (gTTS)
4. 🎞️ Combines each image and audio into individual video clips
5. 🎬 Concatenates all clips into a final video presentation

⚠️ Troubleshooting

Common Issues

• Font Not Found Error: Ensure the specified font file exists in the working directory
• Empty CSV Error: Verify your CSV file contains valid data
• Audio Generation Failure: Check internet connection (required for gTTS)

Font Requirements

The default font is set to "HindVadodara-Light.ttf". If you use a different font:

result = await create_mcq_video(
    csv_file_path="questions.csv",
    font_path="path/to/your/font.ttf"
)

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

👥 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

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Made with ❤️ for educators and content creators