MCP
Model Context Protocol architecture, security patterns, implementation details, and enterprise readiness for MCP deployments.
Adjacent tracks
MCP vs API: what is the difference?
APIs let any two programs communicate. MCP is a standard that lets AI agents discover and call APIs the same way everywhere, without custom wiring for each on
MCP vs A2A: What's the Difference?
MCP connects an agent to tools and data. A2A connects agents to each other. Two complementary protocols for agent systems, and where each one fits.
RAG vs MCP: What's the Difference?
RAG gives a model knowledge from documents; MCP gives an agent tools and live systems. What each does, how they differ, and why most agents use both.
AI agent observability vs evaluation: what each one does
Observability records what your agent did. Evaluation scores whether it was correct. You need both, and most teams only have one.
MCP server vs MCP client: what is the difference?
An MCP server exposes tools, resources and prompts; an MCP client is the connector inside an AI application that talks to one server. The two roles, how a request flows between them, and how to tell whether the agent behind the client is calling the right tools.
MCP vs LLM: what is the difference?
An LLM decides what to do next; MCP carries its tool calls to outside systems and brings the results back. How the two fit together, what goes wrong when they do, and how to evaluate an agent that uses MCP.