Background: Multi-marker metabarcoding is increasingly being used to generate biodiversity information across different domains of life from microbes to fungi to animals such as in ecological and environmental studies. Current popular bioinformatic pipelines support microbial and fungal marker analysis, while ad hoc methods are used to process animal metabarcode markers from the same study. The purpose of this paper is to introduce MetaWorks, a "meta"barcode pipeline that does "the works" and supports the bioinformatic processing of various metabarcoding markers including rRNA and their spacers as well as protein coding loci. Results: MetaWorks provides a Conda environment to quickly gather most of the programs and dependencies for the pipeline. MetaWorks is automated using Snakemake to ensure reproducibility and scalability. We have supplemented existing RDP-trained classifiers for SSU (prokaryotes), ITS (fungi), and LSU (fungi) with trained classifiers for COI (eukaryotes), rbcL (diatoms or eukaryotes), SSU (diatoms or eukaryotes), and 12S (fish). MetaWorks can process rRNA genes, but it can also properly handle ITS spacers by trimming flanking conserved rRNA gene regions, as well as handle protein coding genes by removing obvious pseudogenes. Conclusions: As far as we are aware, MetaWorks is the first flexible multi-marker metabarcode pipeline that can accommodate rRNA genes, spacer, and protein coding markers in the same pipeline. This is ideal for large-scale, multi-marker studies to provide a harmonized processing environment, pipeline, and taxonomic assignment approach. Updates to MetaWorks will be made as needed to reflect advances in the underlying programs, reference databases, or hidden Markov model (HMM) profiles for pseudogene filtering. Future developments will include support for additional metabarcode markers, RDP trained reference databases, and HMM profiles for pseudogene filtering.