MCP Servers 4zu

🚀 MCP Servers

This repository contains a collection of Model Context Protocol (MCP) servers for enhancing the custom capabilities of AI assistants. Each subdirectory holds an independent MCP implementation for a specific use case.

🚀 Quick Start

What is MCP?

Model Context Protocols (MCPs) enable AI assistants to access external tools, data sources, and capabilities beyond their basic knowledge. MCPs empower AI models to:

• Access up-to-date information from external sources.
• Perform specialized tasks and computations.
• Access proprietary or private data.
• Interface with specific tools and systems.

Available MCPs

Great Learning MCP

Location: great_learning/

The Great Learning MCP allows AI assistants to access and search information about Great Learning's educational courses and programs. Features include:

• Semantic search on Great Learning content.
• Detailed information on specific courses.
• Course comparison functionality.
• Full access to Great Learning documents.

View the Great Learning MCP README

Adding MCPs to Your AI Assistant

To use these MCPs with your AI assistant, add the configuration to the assistant's MCP configuration file:

Supported Platforms

• Cursor: ~/.cursor/mcp.json
• Windsurf: ~/.codeium/windsurf/mcp_config.json
• Claude Desktop: ~/Library/Application\ Support/Claude/claude_desktop_config.json
• Claude Code: ~/.claude.json

Configuration Format

{
    "mcpServers": {
        "great-learning-mcp": {
            "command": "/path/to/python/virtualenv",
            "args": [
                "/path/to/mcp-servers/great_learning/great_learning_mcp.py"
            ]
        }
    }
}

📦 Installation

Requirements

• Python 3.12+
• Poetry for dependency management
• Required dependencies for specific MCPs

Steps

1. Clone this repository:

   git clone https://github.com/yourusername/mcp-servers.git
   cd mcp-servers
   

2. Install Poetry if you haven't already:

   curl -sSL https://install.python-poetry.org | python3 -
   

3. Install dependencies:

   poetry install
   

4. Install the specific requirements for each MCP (see individual READMEs).

🔧 Development

To add a new MCP to this repository:

1. Create a new directory for your MCP.
2. Implement your MCP using the MCP SDK.
3. Add a README.md file with usage instructions.
4. Add an mcp_config.json file with configuration details.
5. Add any other required files.