Finding the clique of maximum cardinality in an arbitrary graph is an NP-Hard problem that has many applications, which has motivated studies to solve it exactly despite its difficulty. The great majority of algorithms proposed in the literature are based on the Branch and Bound method. In this paper, we propose an exact algorithm for the maximum clique problem based on the Russian Dolls Search method. When compared to Branch and Bound, the main difference of the Russian Dolls method is that the nodes of its search tree correspond to decision subproblems, instead of the optimization subproblems of the Branch and Bound method. In comparison to a first implementation of this Russian Dolls method from the literature, several improvements are presented. Some of them are adaptations of techniques already employed successfully in Branch and Bound algorithms, like the use of approximate coloring for pruning purposes and bit-parallel operations. Two different coloring heuristics are tested: the standard greedy and the greedy with recoloring. Other improvements are directly related to the Russian Dolls scheme: the adoption of recursive calls where each subproblem (doll) is solved itself via the same principles than the Russian Dolls Search and the application of an elimination rule allowing not to generate a significant number of dolls. Results of computational experiments show that the algorithm outperforms the best exact combinatorial algorithms in the literature for the great majority of the dense graphs tested, being more than twice faster in several cases.