Purpose To study the metagenomics of the microbes isolated from the canaliculus of patients with infective canaliculitis. Methods A prospective study was performed on five consecutive canalicular samples obtained for the metagenomic analysis from the patients with infective canaliculitis who underwent non-incisional canalicular curettage at a tertiary care Dacryology service. The canalicular concretions were collected intraoperatively soon after a canalicular curettage and immediately transported on ice to the laboratory. Following DNA extraction and library preparation, a whole shotgun metagenome sequencing was performed on the Illumina™ platform. The downstream processing and bioinformatics of the samples were performed using multiple software packaged in SqueezeMeta™ pipeline or MG-RAST™ pipeline. Results The taxonomic hit distribution across the samples showed that bacteria were the most common isolates (mean—80.5%), followed by viruses (mean—0.74%), and archaea (0.01%). The five major phyla identified across the samples of infective canaliculitis were, Fusobacteria, Bacteroidetes, Proteobacteria, Actinobacteria, and Firmicutes. The prevalent organisms include Fusobacterium nucelatum, Fusobacterium periodonticum, Parvimonas micra, Prevotella oris, Selonomonas noxia, Pseudopropionobacterium propoinicum, Campylobacter showae, and Streptococcus anginosus, amongst few others. Actinomycetes israelii was noted in all the samples, though it was not the most abundant. The microbial gene mapping and protein prediction demonstrated proteins with known functions to range from 69.91% to 87.09% across the samples. The functional subsystem profiling demonstrated genes associated with carbohydrate, amino acid, and co-enzyme transport and metabolism, cell wall or cell membrane biogenesis, energy production and conversion, transcription, translation, and cellular communications. Conclusion This is the first whole metagenome sequencing of infective canaliculitis. Infected canaliculi harbor diverse microbial communities, including bacteria, viruses, and archaea. Functional analysis has provided newer insights into the ecosystem dynamics and strategies of microbial communities.