How to Design MCP Tool Schemas That Prevent AI Agent Misuse

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A software development analysis highlights that input validation alone is insufficient to prevent AI agents from misusing MCP server tools, as language models can send well-formed but semantically incorrect calls. Four recurring failure patterns are identified: selecting the wrong tool, passing valid-but-incorrect arguments, violating preconditions, and receiving unrecoverable errors. The author argues these are interface design flaws rather than validation bugs, and that the solution lies in constraining tool schemas at the design stage. Using real code from the Frihet MCP server, the piece demonstrates how replacing open string fields with enums and bounded numeric ranges eliminates entire categories of agent error. By making illegal states unrepresentable in the schema itself, developers can guide probabilistic AI callers toward correct behavior without relying on documentation.

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