EVChargeEnv is a lightweight RL environment that simulates electric vehicle charging under uncertain grid load and fluctuating electricity pricing. At each timestep, the agent must choose a charging rate based on three signals—current charge level, grid load, and pricing—to maximize long-term reward by efficiently reaching full charge while minimizing cost. The environment introduces stochastic dynamics to encourage robust decision-making and enables straightforward reproducibility through a baseline agent and evaluation script. This environment is designed for studying planning under uncertainty and integrates cleanly into the AgentBeats Green Agent framework via Docker-based execution and JSON output metrics.