MCP vs Skill: An Evolutionary Perspective

When people compare MCP and Agent Skills , the conversation usually turns into a feature table. Which one supports tools? Prompts? Progressive disclosure? But that framing misses the point. The real story is evolutionary : how our approach to empowering AI agents is shifting — from software engineering to context engineering — and why both MCP and Skills are waypoints on that journey. The Overlap Is Real Let's get the obvious out of the way: MCP and Skills overlap. Every MCP tool could be packaged as a skill. An MCP server that exposes a search_code tool is, in effect, giving the agent a new capability — exactly what a skill does. Look closer and MCP's prompts resemble skill instructions, its resources resemble skill-bundled context. So why do both exist? Because they come from fundamentally different worldviews. MCP Belongs to Software Engineering MCP is the first AI protocol to go truly viral. It has SDKs in TypeScript, Python, Java, Kotlin, C#, and more. Its architecture — client/se