Specifically targeted antimicrobial peptides (STAMPs) are novel alternatives to antibiotics, whereas the development of STAMPs for colonic infections is hindered by limited de novo design efficiency and colonic bioavailability. In this study, we report an efficient de novo STAMP design strategy that combines a traversal design, machine learning model, and phage display technology to identify STAMPs against Clostridium perfringens. STAMPs could physically damage C. perfringens, eliminate biofilms, and self-assemble into nanoparticles to entrap pathogens. Further, a gut-targeted engineering particle vaccine (EPV) was used for STAMPs delivery. In vivo studies showed that both STAMP and EPV@STAMP effectively limited C. perfringens infections and then reduced inflammatory response. Notably, EPV@STAMP exhibited stronger protection against colonic infections than STAMPs alone. Moreover, 16S ribosomal RNA sequencing showed that both STAMPs and EPV@STAMP facilitated the recovery of disturbed gut microflora. Collectively, our work may accelerate the development of the discovery and delivery of precise antimicrobials.