The MAI on TG-2 space laboratory, which was launched on 15 September 2016, is the first on-orbit Multi-angle Polarization Imager in China. The capability of MAI is mainly used to obtain macroscopic and microphysical features of clouds. On-orbit calibration of spaceborne remote sensing instruments is a key prerequisite for the quantitative application of observational data and extends throughout the life of the instrument. Laboratory calibration has been performed prior to MAI launch with high accuracy. In order to monitor the status of MAI after launched, aiming at the problem that MAI has no onboard calibration system, a method of on-orbit monitoring and inter-calibration of TG-2/MAI 565, 670 and 763 nm channels based on Metop-B/GOME-2 hyperspectral data has been presented. The method first obtains the data of same observation target at the similar time and near geometric condition of MAI and GOME-2 based on spatial, temporal and geometric collocation criterion. Then, the GOME-2 reflectance is convoluted with the spectral response function of the MAI visible channels to obtain the reference reflectivity of visible channels. Finally, compare the reference reflectivity with the MAI reflectivity to achieve the onboard calibration of MAI. The process of calibration mainly includes: (1) Forecasting the orbit of TG-2 and Metop-B from December 2016 to February 2017 to obtain the collocated observations between MAI and GOME-2. The temporal matching interval is set to 900 s, and 8 collocated samples of MAI and GOME-2 are obtained, including 2 455 matched pixels. (2) The spatial location of matched pixels is checked, and the cross samples with MAI pixels over 338 covered by a single GOME-2 pixel is reserved to ensure that a single GOME-2 pixel is filled as completly as possible by the MAI pixels. (3) The limit of GOME-2 observation zenith angle is set to 30°, and the geometry of the observation sight detection condition matching pixels is set to the ratio of cosine of the two instruments observed zenith angle is close to 1, and the difference is not more than 0.05, and takes full advantage of MAI multi-angle observation, which allows each MAI pixel with up to 14 viewing angles. Therefore, the optimal matching viewing angle could be chosen; (4) In the target uniformity checking, the condition of uniformity detection for matched pixels is set to the ratio of the reflectance of all MAI piexls coveraged by a GOME-2 piexl standard deviation and the average is less than 0.5. And 469 GOME-2 pixels are reserved. (5) The reflectance of each wavelength corresponding to the above GOME-2 pixels is convoluted with the spectral response function of the MAI visible channel to obtain the corresponding GOME-2 reference reflectance of each MAI channel. (6) Based on the large difference of the spatial resolution of GOME-2 and MAI pixel, the reflectance of all MAI pixels covered by each GOME-2 pixel is averaged and taken as MAI reflectivity, which significantly reduces the dependence of calibration results on target uniformity. (7) And the inter-calibration coefficients are derived by regression analysis of the GOME-2 reference reflectivity and the MAI reflectivity. Onboard inter-calibration of the MAI is achieved. To analyze the influence of matching and screening conditions on the calibration results, the simple variable method is used to adjust the threshold of each test condition in pixel matching and screening process. The results show that the calibration results do not change significantly when the matching and screening conditions are more stringent. The MAI reflectance and the GOME-2 reference reflectance are compared, and the results indicate that both reflectivities have a significant linear relationship with the correlation coefficients all better than 0.97. The mean values of their differences are 1.6%, 4.2% and 2.3%, and the standard deviations are 3.1%, 4.1% and 2.4% for the three channels, respectively. Therefore, on-orbit monitoring and vicarious calibration of the MAI visible bands can be achieved by the inter-calibration method, which lays the foundation for the quantitative application of MAI data.