Multipath congestion control for data center networks has been a research hotspot, but fully utilizing the bandwidth resources of the multipath set remains a significant challenge. This paper proposes a multipath congestion control algorithm based on in-network telemetry (INT), called INTMCC, which leverages detailed link load information to achieve joint optimization of congestion control and load balancing strategies. In INTMCC, in-network telemetry enables the acquisition of both the residual bandwidth of idle paths and the congestion level of congested paths. To achieve more accurate and smoother adjustment of the congestion control window, we design a window adjustment strategy based on the average load of idle paths and that of congested paths. Considering the varying residual bandwidth across idle paths, we derive a fine-grained load balancing scheme that aims to minimize data transmission time within a short time interval. This scheme enables us to obtain the probability of using each entropy and effectively utilize the heterogeneous residual bandwidth across different paths. Given the varying congestion levels across different paths, we assign customized suspension duration to each path to prevent further congestion exacerbation or link underutilization. Simulation results in the htsim environment show that INTMCC achieves significant performance improvements compared to STrack and SMaRTT-REPS in scenarios such as link failures and link degradation, reducing flow completion time by up to 9% in certain cases.