The expansion of cloud-based shared storage increases data privacy concerns. While data encryption technologies can safeguard data content, they cannot prevent the leakage of data access patterns. By re-encrypting data and changing storage location after each access, Oblivious Random Access Machine (ORAM) can effectively avoid information leakage from memory access patterns. While ORAM was initially designed for single-user applications, most existing multi-user ORAM solutions have drawbacks, such as dependence on a trusted proxy, high client storage overhead, and low throughput. To address the issues of multi-user ORAM systems, this paper explores the design of proxyless ORAM solutions in shared storage scenarios and proposes MC-ORAM, a new multi-user oblivious data storage framework. It ensures data consistency through client collaboration in a proxyless architecture, achieves higher throughput by differentiating request processing based on privacy protection requirements, and uses recursion for optimization. We implemented MC-ORAM and analyzed its performance using a variety of indicators, as well as conducting comparative evaluations against alternative schemes. The results show that, on average, MC-ORAM reduces response latency by 18.1% and improves throughput by 23.8% compared to TaoStore.