Depression, as a global psychological disorder, is one of the important factors that cause human health, economic or social burden. Researches have shown that metabolism disorders caused by immune system diseases (i.e. diabetes, crohn disease, irritable bowel syndrome) are closely related to depression. There are large numbers of microbes in human micro-ecological environment. The metabolites of these microbes can also affect as the neurochemical and inflammatory factors in the human brain through the human brain-gut axis, which further affect the emergence of depression. In recent years, researches on the association between microbial metabolism and depression have been published in scientific literature, Wikipedia pages and other biological databases. But few efforts have been made to curate them as structured knowledge, which will make more convenient for the biological and medical community. In this research, we propose and construct a model of knowledge graph linking all metabolism entities of human and their microbes to depression disorder (called MDepressionKG). MDepressionKG has the following advantages: (1) It integrates the human microbial metabolism network, human diseases, microbes and other fields ontologies. (2) The knowledge graph provides a semantic-based logical reasoning for generating potential associations automatically. (3) Various applications such as the discovery of depression comorbidities can be applied as case studies to provide explorations for further depression intervention. The friendly interactive platform for knowledge retrieval and visualization, which is freely available at the URL at http://microbekg.msbio.pro/explore/MDepressionKG.