Data-driven materials discovery to accelerate the development of new catalysts for the green transition shows great promise, but requires machine-interpretable experimental data. For this purpose, we compiled the TheMeCat dataset for the thermocatalytic conversion of CO₂ to methanol. TheMeCat is curated from experimental literature sources, and designed for hybrid computational and experimental catalyst workflows. The dataset captures key catalyst features, process parameters, and methanol conversion efficiencies. Upon detailed analysis of the generated dataset and the associated variability in reported values, we perform targeted error analysis to assess consistency and reinforce the need for clear, structured reporting.