Agent Context Windows Stay Smart with Progressive Discovery MCP Server

AI agents face a "needle in a haystack" problem where large context windows can still lead to confusion and errors when too many tools are loaded. The Model Context Protocol (MCP) with "Progressive Discovery" offers a solution by allowing agents to dynamically load only the necessary tools and context for a specific task, much like a file system. This approach improves performance by reducing token usage and latency, while also increasing accuracy by preventing the model from getting confused by irrelevant tool definitions. By making the agent's reasoning process more structured and predictable, this method also helps build user trust, which is crucial for adoption in sensitive domains like finance.