Accurate diagnosis and classification of kidney cancer are crucial for high-quality healthcare services. However, the current diagnostic platforms remain challenges in the rapid and accurate analysis of large-scale clinical biosamples. Herein, we fabricated a bifunctional smart nanoplatform based on tannic acid-modified gold nanoflowers (TA@AuNFs), integrating nanozyme catalysis for colorimetric sensing and self-assembled nanoarray-assisted LDI-MS analysis. The TA@AuNFs presented peroxidase (POD)- and glucose oxidase-like activity owing to the abundant galloyl residues on the surface of AuNFs. Combined with the colorimetric assay, the TA@AuNF-based sensing nanoplatform was used to directly detect glucose in serum for kidney tumor diagnosis. On the other hand, TA@AuNFs could self-assemble into closely packed and homogeneous two-dimensional (2D) nanoarrays at liquid-liquid interfaces by using Fe3+ as a mediator. The self-assembled TA@AuNFs (SA-TA@AuNFs) arrays were applied to assist the LDI-MS analysis of metabolites, exhibiting high ionization efficiency and excellent MS signal reproducibility. Based on the SA-TA@AuNF array-assisted LDI-MS platform, we successfully extracted metabolic fingerprints from urine samples, achieving early-stage diagnosis of kidney tumor, subtype classification, and discrimination of benign from malignant tumors. Taken together, our developed TA@AuNF-based bifunctional smart nanoplatform showed distinguished potential in clinical disease diagnosis, point-of-care testing, and biomarker discovery.