Alteration of glycosylation in cancer cells leads to the expression of tumor-associated glycans, which can be used as biomarkers for diagnosis and prognostic prediction of diseases. In this study, we used nano-LC-QToF to identify serum N-glycan biomarkers for the detection of brain tumors. We observed an increase in sialylated N-glycans and a decrease in fucosylated N-glycans in the serum of patients with glioblastoma (GBM) and meningioma (MG) compared to healthy individuals. In GBM, a combination of increased serum sialylated N-glycan (6_4_0_2 compound) and decreased fucosylated N-glycan (4_4_1_0 compound) was identified as the most appropriate panel, with an area under the curve (AUC) of 0.8660, 78.95% sensitivity, 84.21% specificity, and 82.89% accuracy. For MG, a combination of decreased 6_6_2_0 and 5_5_2_0 compounds and increased 4_4_1_1 compound achieved an AUC of 0.9260, 82.35% sensitivity, 78.57% specificity, and 80.26% accuracy for diagnosis of MG. Additionally, an increase in 5_5_1_0 and 4_3_0_0 compounds combined with a decrease in 7_7_4_3 was associated with high-grade MG (WHO grades II-III). In conclusion, we identified serum N-glycan profiles associated with brain tumors, highlighting their potential as biomarkers for the diagnosis and prognosis of these diseases.