Human glycoproteins exhibit enormous heterogeneity at each N-glycosite, but few studies have attempted to globally characterize the site-specific structural features. We have developed GlycoProteome Analyzer (GPA) for automated identification and quantitation of site-specific N-glycosylation including mapping system for complex N-glycoproteomes, which combines methods for tandem mass spectrometry with a database search and algorithmic suite. Using an N-glycopeptide database constructed, we created novel scoring algorithms with decoy glycopeptides with three steps: 1) selection of N-glycopeptide from 15 glycan-specific oxonium ions using HCD-MS/MS spectra; (M-score); 2) selection of candidates by matching the isotope pattern to intact N-glycopeptides in the GPA-DB (S-score); and 3) identification of N-glycopeptide from CID and HCD-MS/MS fragment ions (Y-score) with (FDR) < 1%. For example, 95 N-glycopeptides from standard α 1-acid glycoprotein were identified with 0% false positives, giving the same results as manual validation. Additionally automated label-free quantitation method was first developed that utilizes the combined intensity of top three isotope peaks at three highest MS spectral points. IQ-GPA allows direct analysis of site-specific N-glycopeptides with estimated FDR ≤ 1% using a decoy database of target glycopeptide candidates from complex glycoprotein mixtures. We automatically identified and simultaneously quantified about 600 site-specific N-glycopeptides from 123 glycoproteins, which mark the largest number reported to date, spanning five orders of magnitude in concentration from immunoglobulin G to AFP in human plasma. Thus, IQ-GPA platform could make a major breakthrough in high-throughput mapping of complex N-glycoproteomes.