MCP authorization leverages several OAuth specifications to enable secure access to Large Language Models (LLMs) and their integration with remote services. The article outlines the progression from local-only MCP servers to a robust framework that includes dynamic registration, metadata discovery, and the use of PKCE for secure interactions. These advancements facilitate a seamless experience for users wishing to connect their LLMs with various tools without complex configurations.

The guide details how to secure an MCP server using OAuth 2.1 and PKCE, emphasizing the importance of authentication and authorization in managing access for AI-powered applications. It covers the architecture of MCP, the evolution of its authentication methods, and the implementation of secure token handling and role-based access control. By following the guide, developers can create systems that are both secure and user-friendly.