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alexandrekumagae

MCP Content Curation Server

by alexandrekumagae
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TypeScript
Remote

🎓 MCP Content Curation Server

Node.js TypeScript OpenAI 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

Related MCP server: OpenEdu MCP Server

🚀 Quick Start

Prerequisites

  • Node.js 18+

  • OpenAI API key

Installation

  1. Clone the repository

    git clone https://github.com/yourusername/mcp-content-curation-server.git cd mcp-content-curation-server

  2. Install dependencies

    npm install

  3. Configure environment

    cp .env.example .env # Edit .env and add your OpenAI API key

  4. Run the server

    # Development mode npm run dev # Production mode npm run build npm start

🔧 OpenAI Setup

  1. Get your API key from OpenAI Platform

  2. Add it to your .env file:

    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 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
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