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Background: One of the essential resources for developing new drugs are naturally derivedbiologically active lead compounds. Biomedical researchers and pharmaceutical companies arehighly interested in these plant-derived molecules to develop the new drug. In this process, collectiveinformation of the plants and their phytoconstituents with different properties and descriptors wouldgreatly benefit the researchers to identify the hit, lead or drug-like compound. Aim and Objective: Therefore, the work intended to develop a unique and dynamic database Green-MolBD to provide collective information regarding medicinal plants, such as their profile, chemicalconstituents, and pharmacological evidence. We also aimed to present information of phytoconstituents,such as in silico description, quantum, drugability and biological target information. Methods: For data mining, we covered all accessible literature and books, and for in silico analysis,we employed a variety of well-known software and servers. The database is integrated by MySQL,HTML, PHP and JavaScript. Results: GreenMolBD is a freely accessible database and searchable by keywords, plant name, synonym,common name, family name, family synonym, compound name, IUPAC name, InChI Key,target name, and disease name. We have provided a complete profile of individual plants and eachcompounds physical, quantum, drug likeliness, and toxicity properties (48 types descriptor) usingin silico tools. A total of 1846 associated targets related to 6,864 compounds already explored indifferent studies are also incorporated and synchronized. Conclusion: This is the first evidence-based database of bioactive molecules from medicinal plantsspecially grown in Bangladesh, which may help explore and foster nature-inspired rational drug discovery.