An efficient method is introduced for discovering minimal functional dependencies from large database. It is based on the concept of agree sets. From agree sets, maximal sets and its complements are derived, and all minimal non-trivial functional dependencies can be generated. The computation of agree sets can be decreased by using stripped partition database. A levelwise algorithm is used for computing the left hand sides of minimal non-trivial functional dependencies. This method can be used to attribute reduction, clustering and mining associate rules, etc. in knowledge discovery as well as reorganization and design of databases.