Stellar variability in the near-infrared (NIR) remains largely unexplored. The exploitation of public science archives with data-mining methods offers a perspective for the time-domain exploration of the NIR sky. We perform a comprehensive search for stellar variability using the optical-NIR multi-band photometric data in the public Calibration Database of the WFCAM Science Archive (WSA), with the aim of contributing to the general census of variable stars, and to extend the current scarce inventory of accurate NIR light curves for a number of variable star classes. We introduce new variability indices designed for multi-band data with correlated sampling, and apply them for pre-selecting variable star candidates, i.e., light curves that are dominated by correlated variations, from noise-dominated ones. Pre-selection criteria are established by robust numerical tests for evaluating the response of variability indices to colored noise characteristic to the data. We find 275 periodic variable stars and an additional 44 objects with suspected variability with uncertain periods or apparently aperiodic variation. Only 44 of these objects had been previously known, including 11 RR~Lyrae stars in the outskirts of the globular cluster M3 (NGC~5272). We provide a preliminary classification of the new variable stars that have well-measured light curves, but the variability types of a large number of objects remain ambiguous. We classify most of the new variables as contact binary stars, but we also find several pulsating stars, among which 34 are probably new field RR~Lyrae and 3 are likely Cepheids. We also identify 32 highly reddened variable objects close to previously known dark nebulae, suggesting that these are embedded young stellar objects. We publish our results and all light-curve data as the WFCAM Variable Star Catalog.
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