MCP Content Curation Server

# 🎓 MCP Content Curation Server [](https://nodejs.org/) [](https://www.typescriptlang.org/) [](https://openai.com/) [](LICENSE) A **Model Context Protocol (MCP)** server for intelligent course content curation powered by **GPT-4**. This server provides AI-driven tools to categorize, tag, and improve educational content. ## ✨ Features - **🗂️ Smart Categorization**: AI-powered category suggestions for course content - **🏷️ Intelligent Tagging**: Context-aware tag recommendations using GPT-4 - **✨ Content Optimization**: Improve titles and descriptions following best practices - **🔌 MCP Integration**: Seamless integration with Claude Desktop and other MCP clients ## 🚀 Quick Start ### Prerequisites - Node.js 18+ - OpenAI API key ### Installation 1. **Clone the repository** ```bash git clone https://github.com/yourusername/mcp-content-curation-server.git cd mcp-content-curation-server ``` 2. **Install dependencies** ```bash npm install ``` 3. **Configure environment** ```bash cp .env.example .env # Edit .env and add your OpenAI API key ``` 4. **Run the server** ```bash # Development mode npm run dev # Production mode npm run build npm start ``` ## 🔧 OpenAI Setup 1. Get your API key from [OpenAI Platform](https://platform.openai.com/api-keys) 2. Add it to your `.env` file: ```bash OPENAI_API_KEY=sk-your-actual-api-key-here ``` ## 🖥️ Claude Desktop Integration Update your `claude_desktop_config.json`: **Development Mode:** ```json { "mcpServers": { "content-curation": { "command": "npx", "args": ["tsx", "/path/to/your/project/src/server.ts"], "cwd": "/path/to/your/project", "env": { "NODE_ENV": "development" } } } } ``` **Production Mode:** ```json { "mcpServers": { "content-curation": { "command": "node", "args": ["/path/to/your/project/dist/server.js"], "cwd": "/path/to/your/project", "env": { "NODE_ENV": "production" } } } } ``` ## 🛠️ Available Tools ### 1. `suggest_category` Suggests the most appropriate category for course content. **Input:** ```json { "title": "Python for Data Science", "description": "Learn data analysis with pandas and matplotlib" } ``` ### 2. `suggest_tags` Recommends relevant tags based on course content. **Input:** ```json { "title": "Digital Marketing Fundamentals", "description": "Master SEO, Google Ads, and social media marketing" } ``` ### 3. `improve_content` Optimizes titles and descriptions following educational best practices. **Input:** ```json { "title": "JavaScript Basics", "description": "Learn programming fundamentals" } ``` ## 📊 Data Structure The server includes: - **5 main categories**: Technology, Business, Design, Marketing, Analytics - **18 contextual tags**: Organized by subject area - **10 sample courses**: For similarity analysis and training ## 💡 Usage Examples ### Categorization ``` Suggest a category for: "Advanced React Hooks" - "Custom hooks and performance optimization in React" ``` ### Tagging ``` What tags would you recommend for: "Machine Learning with Python"? ``` ### Content Improvement ``` Improve this content: Title: "Excel Basics" Description: "Learn spreadsheets" ``` ## 🛠️ Development ### Available Scripts - `npm run dev` - Start development server - `npm run build` - Compile TypeScript - `npm start` - Run production server - `npm run debug` - Run diagnostics ### Project Structure ``` src/ ├── server.ts # Main MCP server ├── services/ │ ├── ai.service.ts # OpenAI GPT-4 integration │ └── curation.service.ts # Curation logic ├── data/ │ └── mock-data.ts # Categories, tags, and sample data └── types.ts # TypeScript definitions ```