4 rules to build an efficient MCP server

While some developers claim that the Model-Context Pairing (MCP) is outdated in favor of the Skills + CLI approach, the article argues that MCP remains essential for exposing product capabilities through AI assistants, despite issues such as context bloat due to design choices. Context bloat arises not from MCP itself but from how MCP servers are built, with too many tools, verbose descriptions, and oversized payloads contributing to inefficient context usage. To address this, the article suggests treating MCP servers as user interfaces designed for end users rather than APIs, focusing on user intentions, optimizing tool numbers and descriptions, and aggressively filtering responses to reduce token usage. By refining these aspects, MCP servers can be made more lightweight, reliable, and user-friendly, ultimately improving the decision-making capabilities of language models. The article emphasizes the importance of testing and iterating quickly to refine MCP server functionality and introduces Bump.sh as a tool for quickly describing and publishing MCP servers to enhance user experience and performance.