EduTrendAnalytics

EduTrendAnalytics is a Next.js-based platform for tracking and analyzing technology trends from GitHub, Hugging Face, and Smithery AI. It combines features from GrimoireLab, LangSmith, and Cauldron, integrating with APIs, n8n automation, and MCP servers to provide educational insights into developer interests, focus, and technology mega-trends.

Features

• Data Collection: Fetches recent repositories from GitHub, models from Hugging Face, and MCP servers from Smithery AI.
• Sector Analysis: Classifies additions by sector (AI/ML, Automation, Web Development, etc.) and calculates distribution percentages.
• Trend Visualization: Displays results in interactive tables and charts on a dashboard.
• Educational Modules: Provides training lessons on analyzing tech trends and understanding mega-trends.
• MCP Integration: Utilizes Smithery AI's Model Context Protocol for AI agent tasks.

Project Goals

This project aims to:

1. Track and analyze new additions from technology platforms to identify sector trends
2. Provide educational content to help users understand and interpret technology trends
3. Demonstrate practical applications of combined features from GrimoireLab, LangSmith, and Cauldron
4. Integrate with n8n for workflow automation and MCP for AI agent capabilities

Getting Started

Prerequisites

• Node.js 18.x or later
• npm or yarn
• GitHub API token (optional, for higher rate limits)
• Hugging Face API token (optional)

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/edutrendanalytics.git
   cd edutrendanalytics
   

2. Install dependencies:

   npm install
   

3. Create a .env.local file in the root directory with your API tokens (optional):

   GITHUB_TOKEN=your_github_token
   HUGGINGFACE_TOKEN=your_huggingface_token
   

4. Start the development server:

   npm run dev
   

5. Open http://localhost:3000 in your browser.

Project Structure

• /src/app: Next.js app pages
• /src/components: React components
• /src/lib: Utility functions for API calls and data analysis
• /src/types: TypeScript type definitions

Usage

Dashboard

Visit the /dashboard page to:

• View recent technology additions in a table
• Explore sector distribution with visual charts
• Analyze mega-trends and developer interests

Training Modules

Visit the /training page to:

• Access educational content on tech trend analysis
• Learn about AI/ML trends, automation with MCP, and interpreting mega-trends
• Follow hands-on examples with case studies

Customization

You can customize various aspects of the project:

• Modify the sector classification logic in src/lib/api.ts
• Add new training modules in src/app/training/page.tsx
• Extend visualizations in the dashboard with additional charts

Deployment

This project can be deployed on Vercel or any other Next.js-compatible hosting:

npm run build
npm start

License

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

Acknowledgements

• GrimoireLab for inspiration on software development analytics
• LangSmith for concepts on LLM analytics
• Cauldron for community analytics approaches
• Smithery AI for MCP server concepts
• n8n for workflow automation integration