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MCP Content Curation Server

A Model Context Protocol (MCP) server for intelligent course content curation powered by GPT-4. Provides AI-driven tools to categorize, tag, and improve educational content with seamless Claude Desktop integration.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "alexandrekumagae-ai-content-categorization-mcp": {
      "command": "node",
      "args": [
        "/path/to/your/project/dist/server.js"
      ],
      "env": {
        "NODE_ENV": "production",
        "OPENAI_API_KEY": "sk-your-actual-api-key-here"
      }
    }
  }
}

The MCP Content Curation Server is an AI-powered assistant that helps you categorize, tag, and optimize educational content. By leveraging GPT-4, it streamlines how you organize course materials so students find relevant content faster and educators save time refining titles and descriptions.

How to use

You connect an MCP client to the server to access its AI-powered curation features. Use it to autocomplete or suggest a category for a course, propose relevant tags based on the content, and improve titles and descriptions to follow educational best practices.

Practical usage patterns you can rely on include: selecting a course title and description, asking for an automatic category suggestion, requesting a set of context-aware tags, and prompting an optimization pass to tighten the title and expand the description for clarity and searchability.

How to install

Prerequisites you need before installation.

• Node.js 18+ is required.

• An OpenAI API key for GPT-4 access.

Step-by-step commands to set up the MCP server.

# 1. Clone the project
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

Configuration, security, and usage notes

OpenAI integration relies on your API key. You will store it in the environment and use it to power the AI features.

If you are using Claude Desktop for MCP integration, you can point the client to run the server in development or production mode as shown in the example configurations.

Development and production runtime options are shown below so you can adapt to your environment.

Environment variable NODE_ENV controls the runtime mode, and OPENAI_API_KEY provides access to GPT-4.

Available tools

suggest_category

Suggests the most appropriate category for course content including title and description context.

suggest_tags

Recommends relevant tags based on the course content to improve discoverability and relevance.

improve_content

Optimizes titles and descriptions following educational best practices for clarity and searchability.