Why LLM Agents Need Deterministic Tools for Exact Fraction Arithmetic

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Large language models predict tokens statistically, so they can err on precise calculations such as multiplying fractions. The article argues that this weakness is a liability in fields like engineering, finance, and scientific computing. Standard floating-point arithmetic also introduces rounding drift because some decimals cannot be represented exactly. The author proposes routing exact math to external tools via the Model Context Protocol, including a fractions connector that parses, computes, and simplifies rational numbers using integer arithmetic. The piece also discusses deploying such connectors reliably through the Vinkius platform and the open-source MCPFusion framework.

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