Large Language Models (LLMs) discover MCP (Model-Compute Provider) servers through metadata endpoints, orchestration tools, or APIs that broadcast available resources. These servers expose capabilities like compute power, storage, and model compatibility, enabling LLMs to select and connect dynamically for optimal performance, scalability, and resource allocation during inference or training.