Aim: To develop a web tool for survival analysis based on CpG methylation patterns. Materials & methods: We utilized methylome data from ‘The Cancer Genome Atlas’ and used the Cox proportional-hazards model to develop an interactive web interface for survival analysis. Results: MethSurv enables survival analysis for a CpG located in or around the proximity of a query gene. For further mining, cluster analysis for a query gene to associate methylation patterns with clinical characteristics and browsing of top biomarkers for each cancer type are provided. MethSurv includes 7358 methylomes from 25 different human cancers. Conclusion: The MethSurv tool is a valuable platform for the researchers without programming skills to perform the initial assessment of methylation-based cancer biomarkers.