Metaproteomics characterizes proteins expressed by microorganism communities (microbiome) present in environmental samples or a host organism (e.g. human), revealing insights into the molecular functions conferred by these communities. Compared to conventional proteomics, metaproteomics presents unique data analysis challenges, including the use large protein databases derived from hundreds of organisms, as well as numerous processing steps to ensure data quality. This data analysis complexity limits the use of metaproteomics for many researchers. In response, we have developed an accessible and flexible metaproteomics workflow within the Galaxy bioinformatics framework. Via analysis of human oral tissue exudate samples, we have established a modular Galaxy-based workflow that automates a reduction method for searching large sequence databases, enabling comprehensive identification of host proteins (human) as well as meta-proteins from the non-host organisms. Downstream, automated processing steps enable BLASTP analysis and evaluation/visualization of peptide sequence match quality, maximizing confidence in results. Outputted results are compatible with tools for taxonomic and functional characterization (e.g. Unipept, MEGAN5). Galaxy also allows for the sharing of complete workflows with others, promoting reproducibility and also providing a template for further modification and improvement. Our results provide a blueprint for establishing Galaxy as a solution for metaproteomic data analysis.