LLMs work better with the right context, and there are two main ways to extend their capabilities: Model Context Protocol (MCP) servers and skills. MCP standardizes how AI agents connect to external data sources like CRMs, databases, and cloud APIs, handling authentication and structured tool calls. Skills are reusable markdown-based instruction sets that teach models domain-specific behavior, auto-loading into the context window only when relevant. MCP is best when the value comes from real-time external data access, while skills shine for consistent formatting, repeated workflows, and domain expertise. The two approaches are complementary — effective AI agents often use MCP for system access and skills for process knowledge.
Table of contents
Why LLMs need contextConnecting external data with the Model Context ProtocolAdding domain expertise with skillsWhen to use MCP serversWhen to use skillsCombining MCP and skills for comprehensive workflowsNext steps for your automation architectureSort: