We develop a membrane clustering algorithm to deal with automatic clustering problem. We design a tissue-like membrane system with fully connected structure. This system is capable of adapting to the changing environment and learning from the data. The algorithm is designed to be efficient and scalable, making it suitable for large datasets. By using this algorithm, we can automatically group similar data points together, which can be useful in various applications such as data mining and machine learning.