  The fast and affordable sequencing of large clinical and environmental
metagenomic datasets opens up new horizons in medical and biotechnological
applications. It is believed that today we have described only about 1\% of the
microorganisms on the Earth, therefore, metagenomic analysis mostly deals with
unknown species in the samples. Microbial communities in extreme environments
may contain genes with high biotechnological potential, and clinical
metagenomes, related to diseases, may uncover still unknown pathogens and
pathological mechanisms in known diseases. While the species-level
identification and description of the taxa in the samples does not seem to be
possible today, we can search for novel genes with known functions in these
samples, using numerous techniques, including artificial intelligence tools,
like the hidden Markov models (HMMs). Here we describe a simple-to-use
webserver, the MetaHMM, which is capable of homology-based automatic
model-building for the genes to be searched for, and it also finds the closest
matches in the metagenome. The webserver uses already highly successful
building blocks: it performs multiple alignment by applying Clustal Omega,
builds a hidden Markov model with HMMER components of hmmbuild and uses
hmmsearch for finding similar sequences to the specified model in the
metagenomes. The webserver is publicly available at
\url{https://metahmm.pitgroup.org}.
