Beyond Hallucinations: Compass MCP Brings Certainty to AI Dietary Recommendations

LLMs frequently hallucinate about restaurant recommendations, particularly for specialized dietary needs, creating genuine safety risks for users who rely on that guidance. Compass MCP addresses this critical gap by returning structured verdicts (fit, not_fit, or honest "unknown") backed by real menu data, reviews, and deterministic scoring rather than AI generation. This shift from speculative outputs to evidence-grounded answers is especially important for health-related AI applications where accuracy directly impacts user safety.