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The post provides production evidence that the widely cited ~15-tool MCP limit is a proxy for ambiguity rather than a hard count ceiling, and demonstrates that naming grammar, description-level routing instructions, and selection-focused evals can keep a 27-tool server accurate.
Adopt the classifier-as-architectural-gate pattern in your own agentic pipelines to cut costs, improve output quality, and block harmful inputs before they reach expensive or capable models.
Developers building AI coding agents should audit their harness beyond `CLAUDE.md` — implementing `PreToolUse` hooks, MCP tools, permission lists, and observability can yield double-digit reliability gains without touching the underlying model.