Required Knowledge
Model Context Protocol (MCP) - An open standard that lets AI agents discover and call external tools dynamically. Think of it like a USB standard for AI: instead of custom wiring for every integration, any compliant agent can plug into any compliant server and immediately know what it can do.
RAG (Retrieval-Augmented Generation) - A technique where an AI model fetches relevant documents before answering, rather than relying solely on its training data. This keeps answers grounded in current, accurate sources instead of hallucinated facts.
Vector Search - A way of finding documents by meaning rather than exact keywords. Text is converted to numerical embeddings, and search finds the closest matches in that space. "How do I deploy to Azure?" finds relevant results even if the docs say "publish to Azure" instead.
Session Affinity - When a distributed system routes requests from the same client to the same server instance. Important for stateful protocols where the server needs to remember prior messages in a conversation.
Streamable HTTP Transport - A HTTP-based connection pattern where the server can push data back to the client incrementally, useful for long-running AI responses that arrive token by token rather than all at once.