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Model Context Protocol (MCP) Server

by AndreaGriffiths11

AI/Development ToolsProtocolDevelopmentDockerVS Code

The Model Context Protocol (MCP) enables AI models to communicate with development environments. MCP servers act as intermediaries between AI models and development environments, providing a standardized interface for interactions.

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Model Context Protocol (MCP) Tips and Best Practices

What is MCP?

The Model Context Protocol (MCP) is a protocol that enables AI models to communicate with development environments and tools. It allows AI assistants to gather context, execute commands, and make changes to codebases in a structured and secure way. MCP servers act as intermediaries between AI models and development environments, providing a standardized interface for interactions.

Setup Guide

Prerequisites

  • Docker installed on your system
  • GitHub Personal Access Token (PAT) with appropriate permissions
  • VS Code with the necessary extensions

Basic Setup Steps

  1. Environment Configuration

    • Set up your GitHub token as an environment variable: 
      export GITHUB_TOKEN=your_token_here

  2. Docker Image

    • The MCP server runs in a Docker container
    • The official image is available at: ghcr.io/github/github-mcp-server

  3. VS Code Settings

    • Configure the MCP server in your VS Code settings.json
    • Basic configuration example: 
      {
  "mcp": {
    "servers": {
      "github": {
        "command": "docker",
        "args": [
          "run",
          "-i",
          "--rm",
          "-e",
          "GITHUB_PERSONAL_ACCESS_TOKEN=${env:GITHUB_TOKEN}",
          "ghcr.io/github/github-mcp-server"
        ],
        "env": {
          "GITHUB_PERSONAL_ACCESS_TOKEN": "$GITHUB_TOKEN"
        }
      }
    }
  }
}

Configuration Tips

Best Practices

  1. Token Security

    • Never commit your GitHub token to version control
    • Use environment variables for sensitive information
    • Regularly rotate your PAT for security

  2. Docker Configuration

    • Use the --rm flag to automatically remove containers after they stop
    • Consider using volume mounts for persistent data
    • Keep your Docker image updated to the latest version

  3. VS Code Integration

    • Keep your VS Code and extensions updated
    • Configure logging levels appropriately
    • Use workspace-specific settings when needed

Troubleshooting

Common Issues and Solutions

  1. Connection Issues

    • Verify Docker is running
    • Check if your GitHub token is valid and properly set
    • Ensure proper network connectivity to GitHub

  2. Authentication Problems

    • Verify your PAT has the required scopes
    • Check environment variable configuration
    • Ensure the token hasn't expired

  3. Docker-related Issues

    • Clear Docker cache if experiencing image problems
    • Check Docker logs for detailed error messages
    • Verify Docker has sufficient system resources

  4. VS Code Integration Issues

    • Reset VS Code settings to default if needed
    • Check VS Code's extension logs
    • Verify MCP configuration syntax in settings.json

Debugging Tips

  • Enable verbose logging in VS Code
  • Check Docker container logs
  • Verify environment variable availability
  • Monitor system resource usage

Advanced Configuration

Custom Server Configuration

  • Configure multiple MCP servers
  • Set up custom environment variables
  • Configure resource limits

Performance Optimization

  • Configure caching settings
  • Optimize Docker container resources
  • Set appropriate timeout values

Additional Resources