Current glacier model-data comparison methods often lack quantitative, automated validation for reconstructing complex palaeoglaciers and palaeo ice fields over millennia. Rigorous validation and automatic evaluation is critical for improving the reliability of glacier reconstructions and their use in understanding past climate and future projections. We introduce an open-source, Python-based comparison tool (GLAMODAT version 1.0) that automatically evaluates palaeoglacier model simulations against dated constraints on glacier history. GLAMODAT successfully quantifies model-data mismatches and demonstrates robustness in both synthetic and real-world case studies. It effectively tracks multiple phases of advance and retreat periods within mountain valleys. It is designed for validating single palaeoglacier simulations or entire ensembles by integrating weighted misfit scoring and adaptive parameter space exploration. It enables advancements in palaeoglacier reconstructions, climate reconstructions, and parameter studies in glacier modelling.