Large-scale open datasets can accelerate ecological research. In this paper, we developed an LLM-based metadata collector that flexibly extracts metadata from various data providers and transforms it into a user-defined format using existing metadata standards. This tool extracts both structured and unstructured metadata with equal accuracy, further enhancing accuracy through an LLM post-processing protocol. Furthermore, it identifies links between datasets by calculating embedding similarity and unifying the extracted metadata format. The developed tool can be used for ontology creation or graph-based queries, and can be utilized to discover relevant ecological and environmental datasets in virtual research environments.