This article outlines key strategies for creating effective Model Context Protocol (MCP) servers that prioritize user outcomes over traditional API design. It emphasizes the importance of simplifying tool design, providing clear instructions, and curating tools for better agent interaction. The focus is on building a user-friendly interface for AI agents rather than merely replicating REST API structures.

This article outlines best practices for securing the Model Context Protocol (MCP), which links large language models to various tools and data. It provides actionable steps for protecting MCP servers, enforcing access restrictions, and implementing human oversight to minimize risks.