Mesoscale convective systems (MCSs) are active in East China during the summer, causing significant precipitation and extreme weather. Increasing MCS frequency and intensity with climate change highlights the need for better simulation and forecasting. Traditional global and regional models with coarse resolution unable to explicitly resolve convection fail to represent MCSs and their precipitation accurately. This study conducted a 22-year (2000–2021) JJA simulation at a convection-permitting resolution (4 km grid spacing) using the WRF model (WRF-CPM) over East China. The WRF-CPM model’s ability to reproduce MCSs was evaluated against satellite infrared-retrieved cloud top temperature, IMERG V06 precipitation, and global reanalysis data ERA5. Results show that WRF-CPM captures the observed MCS frequency and precipitation patterns but overestimates them in most areas. The model also accurately simulates the eastward propagation of MCSs, albeit at a slightly faster speed and longer duration. MCSs in WRF-CPM exhibit realistic life cycles in terms of cloud top temperature, convective core area, and precipitation. WRF-CPM tends to overestimate rainfall frequency over 20 mm/h while underestimates rainfall per MCS, possibly due to an overestimated number and area. The model captures the diurnal cycle of MCSs well in most of East China, though it shows a 2-hour delay in southeast China and fails to reproduce the midnight peak to the east of Tibetan Plateau, probably because of model’s limited ability to represent thermal diurnal variation over complex topography. WRF-CPM captures the shear effect on MCS precipitation, indicating increased precipitation with stronger shear and higher total column water vapor.