The growth of distributed generation resources, local electricity markets, and peer-to-peer energy exchanges has introduced challenges, notably balancing network technical constraints with maximum utilization of distributed generation units. Static operation envelopes (SOEs) and Dynamic operation envelopes (DOEs) have emerged as solutions, statically and dynamically setting network constraints over time, respectively. However, these envelopes often calculated by distribution system operators (DSOs) and imposed on users, may overlook participants' preferences, reducing profits and incentives to engage in local markets. Addressing this, the paper proposes a framework for determining feasible transaction regions (FTRs), established through agreements between energy communities (ECs) and DSOs. These FTRs represent optimal operating envelopes that consider uncertainties in ECs and DSO constraints. The framework models EC uncertainties using the chance constraint method and solves the optimization problem with the alternating direction method of multipliers (ADMM) on a standard IEEE 69-bus network using GAMS software. Results highlight the method's efficiency and accuracy compared to DOE and SOE approaches, effectively defining safe regions for peer-to-peer energy trading in distribution networks. This novel approach optimizes energy exchanges while respecting technical constraints and participant preferences. Also, this paper, by providing different confidence levels during simulations, verifies the proper efficiency of the proposed method in operating the uncertainty of distributed generations. The simulation results show cost reduction of ECs and loss reduction in the distribution network along with increment in active and reactive power exchanges compared to DOE and SOE methods.