matchcn uses Jev for semantic component search for coding agents
The author built matchcn with Jev, classifying 1,783 components from 9 shadcn registries across six dimensions such as purpose, motion and density, with Jev returning calibrated probabilities that score results so coding agents can search before they generate.
Built matchcn: semantic component search for coding agents, powered by Jev. Describe the UI you need. It finds the component and returns the install command. No component name needed. No browsing 9 different libraries. 1,783 components across 9 @shadcn registries, classified across six dimensions: purpose, motion, density, interaction, data, and decoration. Jev returns calibrated probabilities instead of generated text, so every classification comes with confidence. Matching uses that confidence when scoring results. You can see exactly what matched, what didn't, and how much each dimension contributed. Currently indexing: React Bits @davidhaz, Magic UI @dillionverma, Aceternity @aceternitylabs , Kokonut UI @dorianbaffier, Animate UI @animate_ui, Motion Primitives @Ibelick, assistant-ui @assistantui, bundui @bunduidotio, shadcn-dashboard. (your components, your registries, your install commands, straight from you) The goal: give coding agents a way to search before they generate. @matchcndev http://matchcn.dev