We present FlexControl, a novel approach for flexible and efficient full-body controllable text-to-motion generation in this paper. Unlike previous methods that focus on controlling specific parts of the body, FlexControl enables users to set different control strengths for various joints throughout the body, achieving a balance between motion precision and naturalness. Specifically, our approach is built upon a diffusion network. It introduces the innovative FlexGuide module, an additional control module that allows users to manually balance the influence of text descriptions and trajectory constraints on the generated motion. Furthermore, we propose a novel architecture called MotionAdapter, which dynamically adapts the motion generation process to external control signals while maintaining the integrity of the original text-to-motion model. Additionally, our method demonstrates excellent generation efficiency while maintaining high motion quality, enabling real-time interactive applications. Experimental results demonstrate that FlexControl can achieve high performance on full-body control accuracy, flexibility, generation efficiency, and motion realism.