How to build secure and scalable remote MCP servers

Model Context Protocol (MCP) is a framework that facilitates the connection of AI agents to external tools and data sources by standardizing the integration process, thereby eliminating the need for API-specific connectors. Its key feature is the incorporation of OAuth 2.1 for secure authorization, which allows developers to leverage existing security infrastructure and practices, such as token validation and user authentication, while building MCP servers. The protocol emphasizes robust security measures to prevent vulnerabilities like token reuse and unauthorized access, particularly due to the sensitive nature of the data and tools it connects. Developers are encouraged to use established libraries and frameworks to implement security features, such as dynamic client registration and resource indicators, ensuring tokens are bound to specific servers. As MCP gains adoption, the use of AI gateways is recommended to manage traffic, maintain security, and handle evolving protocol versions. Effective secrets management and observability are also crucial, with emphasis on using dedicated services for secret storage and real-time monitoring to maintain security and performance.