Microrobots for endovascular embolization face challenges in precise delivery within dynamic blood vessels. Here, an intelligent generic high-throughput oscillatory shear technology (iGHOST) is proposed to fabricate diversely programmable, multifunctional microrobots capable of real-time visual guidance for in vivo endovascular embolization. Leveraging machine learning (ML), key synthesis parameters affecting the success and sphericity of the microrobots are identified. Therefore, the ML-optimized iGHOST enables continuous production of uniform microrobots with programmable sizes (400-1000 mu m) at an ultrahigh rate exceeding 240 mL h-1 by oscillatory segmenting fluid into droplets before ionic cross-linking, and without requiring purification. Particularly, the iGHOST-fabricated magnetically responsive lipiodol-calcium alginate (MagLiCA) microrobots are highly distinguishable under X-ray imaging, which allows for precise navigation in fluid flows of up to 4 mL min-1 and accurate embolization in liver and kidney blood vessels, thus addressing the current issues. Crucially, MagLiCA microrobots possess drug-loading capabilities, enabling simultaneous embolization and site-specific treatment. The iGHOST process is an intelligent, rapid, and green manufacturing method, which can produce size-controllable, multifunctional microrobots with the potential for precise drug delivery and treatment under real-time imaging across various medical applications.