The strategy integrated MATLAB automated MS annotation, in vivo chemometric screening, and progesterone assessment under oxidative stress was established for the identification of absorbed bioactive constituents of Cuscuta seed (CS). MATLAB platform characterized 203 components (flavonols, alkaloids, phenolic acids, etc) in CS extract, outperforming commercial software through its combinatorial “parent molecules + group fragments” database and automated neutral loss/diagnostic ion matching. This approach was designed to effectively minimize in-source fragmentation false positives, while its dual-dimension similarity algorithm refined molecular networking. Furthermore, 20 prototypes and 46 metabolites were discovered and identified in plasma and urine after oral administration of CS by OPLS-DA and MATLAB analysis platform. Cuscutamine and p-coumaric acid exhibited high systemic exposure. Based on in vivo metabolic analysis, 9 major absorbed constituents were revealed. Hyperoside, ferulic acid, cuscutamine, kaempferol, and quercetin demonstrated significant bioactivity by attenuating H₂O₂-induced oxidative damage in R2C Leydig cells and restoring progesterone levels.