In real life networks like social and biological networks, the network is said to have community structure if the vertices of the network can be partitioned into groups of nodes such that each group contains the nodes that are densely connected in the original graph that represents this network. These groups are referred to as communities. Detecting and identifying communities in networks is essential in many domains. The paper proposes a simple method for detecting communities that is based on the node clustering coefficient which is a local structural property of the graph underlying the network. The clustering value indicates the clique formation among the node neighbors.