Summary

The article discusses the design challenges and tradeoffs associated with Model Context Protocol (MCP) tools, particularly in the context of large language models (LLMs) and agentic systems. It identifies two primary issues: bloat and confusion, which can degrade performance and lead to inefficient tool calls. The authors present practical context engineering approaches to mitigate these issues, including improving tool descriptions, using schema constraints, and implementing lazy loading techniques. The article includes a code walkthrough demonstrating various MCP tool designs and their impact on performance.

💭 Your Thoughts

- Confusion, Bloat - Back your entire MCP server with an agent of your own

Data Problems Addressed

Technologies Referenced