Vertical search engine of the ministry of agriculture needs to collect the market price data of agricultural products in various years from all over the country. It can not be avoided that the massive agricultural market price data has abnormal price point, which has an impact on the analysis and forecast of the agricultural market price. It needs to be solved to find market price data outliers and calculates the price boundary. Therefore, on the basis of the traditional data mining clustering K-means algorithm, this study achieves the outlier data detection and calculation of the boundary of the price of agricultural products, test and practice results show that the method improves the clustering accuracy and stability and achieves the calculation of the price of outlier detection and border price.