MCP Sampling

MCP sampling is the mechanism by which an MCP server asks the connected AI client to perform an LLM inference call on its behalf, enabling server-side agentic patterns without the server having direct access to a model. Sampling requests must be governed because they allow servers to influence model behaviour and inject content into the agent's reasoning context.