This repository demonstrates the implementation and usage of the Model Context Protocol (MCP) for GitHub integration.
The Model Context Protocol (MCP) is a standardized way to enable AI models to interact with external services and APIs in a controlled and secure manner. It provides a structured interface for AI models to perform actions and receive context from various platforms and services.
- Standardized Interface: MCP provides a consistent way to interact with different services through a unified protocol.
- Security: Authentication and authorization are handled through secure tokens and configurations.
- Extensibility: New services can be added by implementing the MCP interface.
- Context Awareness: Models can receive and maintain context about the current state of the service they're interacting with.
The GitHub MCP integration allows AI models to:
- Create and manage repositories
- Handle issues and pull requests
- Manage files and content
- Access repository information
- Work with branches and commits
- And more...
MCP configuration is typically stored in a JSON format. Here's an example configuration for GitHub integration:
{
"mcpServers": {
"github": {
"command": "npx",
"args": [
"@smithery/cli",
"run",
"@smithery-ai/github",
"--key",
"YOUR_KEY",
"--profile",
"YOUR_PROFILE"
]
}
}
}The GitHub MCP can be used through compatible AI interfaces that implement the protocol. The protocol handles:
- Authentication and authorization
- API rate limiting
- Response formatting
- Error handling
- Context management
- Simplified Integration: No need to handle raw API calls
- Consistent Interface: Standardized way to interact with GitHub
- Security: Proper handling of authentication and sensitive data
- Context Awareness: Maintains state and context across interactions
- Error Handling: Standardized error handling and recovery
- Install the required dependencies
- Configure your MCP settings
- Initialize the GitHub MCP client
- Start making API calls through the protocol