α-Solanine and α-chaconine are the two most predominant glycoalkaloids (GAs) present in potato. Potato peel contains a high concentration of GAs, which are especially interesting for application in the pharmaceutical industry due to their different beneficial properties (such as anticarcinogenic, anti-inflammatory, antiallergic, antipyretic, antiviral, fungicide, and antibiotic activities, among others); so, potato peel waste can be valorized by extracting these biologically active compounds. For this, a green, quick, and efficient miniaturized analytical approach based on ultrasound-assisted extraction (UAE) combined with HPLC-DAD was developed to quantify α-solanine and α-chaconine in potato peel. Some parameters of the extraction were optimized, including the extraction method, the type of solvent, and the sample/solvent ratio, by a three-factor, three-level (33) full factorial experimental design. The optimal extraction conditions were obtained with UAE using methanol as a solvent and a sample/solvent ratio of 1:10 (w/v, g/mL). The analytical greenness metric for sample preparation (AGREEprep) tool was used to assess the greenness of the methods used. The tool revealed an acceptable green analysis, with 0.61 points. The method was validated and applied to the evaluation of GAs in the peel of 15 commercial varieties of potato. The amount of glycoalkaloids found in the samples evaluated ranged from 143 to 1273 mg/kg and from 117 to 1742 mg/kg dry weight for α-solanine and α-chaconine, respectively. These results reveal the important variability that exists between potato varieties; so, their analysis is of great importance to select the most suitable ones for biovalorization (e.g., the Amandine and Rudolph varieties, with around 3000 mg/kg, in total, of both GAs). To provide higher stability to the peel during storage, freeze-drying or a medium-temperature drying process resulted preferable to avoid GA degradation. Overall, this study will contribute to the expansion of the future biovalorization of potato peel waste as well as provide a powerful analytical tool for GA analysis.