This review summarizes the current state of network pharmacology databases for Traditional Chinese Medicine (TCM). Network pharmacology is a systems biology approach that helps understand the complex interactions between TCM compounds, proteins, genes, and diseases. It has become an important tool for studying TCM, especially for understanding the mechanisms of action and safety of TCM preparations. The review discusses various TCM databases and tools used in network pharmacology research, including TCM database@Taiwan, HIT, TCMSP, TCMID, and TCM-Mesh. These databases provide information on TCM compounds, targets, and diseases, and are used to analyze the interactions between TCM ingredients and biological systems. The review also compares the general statistics and search results of these databases, highlighting their strengths and limitations. The authors conclude that while TCM databases have made significant progress, they still need improvement to better support TCM research. Additionally, the review emphasizes the importance of integrating TCM with gut microbiota research to better understand and treat microbiome-related diseases. The study highlights the potential of network pharmacology in advancing TCM research and development, and calls for further improvements in TCM databases to support this goal.This review summarizes the current state of network pharmacology databases for Traditional Chinese Medicine (TCM). Network pharmacology is a systems biology approach that helps understand the complex interactions between TCM compounds, proteins, genes, and diseases. It has become an important tool for studying TCM, especially for understanding the mechanisms of action and safety of TCM preparations. The review discusses various TCM databases and tools used in network pharmacology research, including TCM database@Taiwan, HIT, TCMSP, TCMID, and TCM-Mesh. These databases provide information on TCM compounds, targets, and diseases, and are used to analyze the interactions between TCM ingredients and biological systems. The review also compares the general statistics and search results of these databases, highlighting their strengths and limitations. The authors conclude that while TCM databases have made significant progress, they still need improvement to better support TCM research. Additionally, the review emphasizes the importance of integrating TCM with gut microbiota research to better understand and treat microbiome-related diseases. The study highlights the potential of network pharmacology in advancing TCM research and development, and calls for further improvements in TCM databases to support this goal.