🎓 MCP Content Curation Server
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
-
Clone the repository
git clone https://github.com/yourusername/mcp-content-curation-server.git cd mcp-content-curation-server -
Install dependencies
npm install -
Configure environment
cp .env.example .env # Edit .env and add your OpenAI API key -
Run the server
# Development mode npm run dev # Production mode npm run build npm start
🔧 OpenAI Setup
- Get your API key from OpenAI Platform
- Add it to your
.envfile:OPENAI_API_KEY=sk-your-actual-api-key-here
🖥️ Claude Desktop Integration
Update your claude_desktop_config.json:
Development Mode:
{
"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:
{
"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:
{
"title": "Python for Data Science",
"description": "Learn data analysis with pandas and matplotlib"
}
2. suggest_tags
Recommends relevant tags based on course content.
Input:
{
"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:
{
"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 servernpm run build- Compile TypeScriptnpm start- Run production servernpm 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