Machining of hard materials has been difficult and expensive because of poor surface smoothness, early tool failures, etc. When used in machining hard materials, such as medium and high carbon, cast steels, Inconel, and other alloys, nanomaterials combined with base fluids, such as water and oils, provide superior results in terms of surface finish and low cutting temperatures. To enhance our understanding of the field of machining and its applications, a comprehensive literature assessment on machining steels using nanofluids with/without the minimum quantity lubrication (MQL) approach was conducted. This research aims to investigate the performance of nanofluids (n-Al2O3, n- MoS2, and n-graphene) mixed with coconut oil in various proportions and injected into the tool–work interface using the MQL mist system. Output responses, such as surface roughness values, and cutting temperatures, were measured. The cutting temperatures were determined using an infrared camera and a k-type thermocouple, and the surface roughness was determined using a Talysurf surface meter. Cutting parameters, such as cutting speed, feed rate, and depth of cut, were maintained constant throughout the experiments. The experiments comprised a single factor (MQL fluid) with eight levels. Multiresponse optimization using grey relational coefficients showed that n-Al2O3 and n-MoS2 hybrid combinations with coconut oil yielded better results, i.e., higher ranks, compared with n-graphene mixtures in coconut oils. The experimental findings demonstrated that nanofluids outperformed pure coconut oil. Nano-Al2O3 combined with coconut oil produced a superior surface finish, lowered the cutting temperatures, and ensured minimum chip thickness.