MCP Server: Upload custom model weights from your AI assistant
PreviousAuto Label with Workflows: Label data with any model or custom logicNextMultiple Models Per Version: Train and compare models side by side
Last updated
Was this helpful?
You can now upload locally trained model weights to Roboflow directly from Claude Code, Cursor, or any MCP client, with no manual packaging or upload scripts. Supported architectures include YOLOv5 through YOLOv12, YOLO26, YOLO-NAS, RF-DETR, Florence-2, and PaliGemma.
Weights can be uploaded as a versioned deployment tied to a dataset version, or registered as a workspace model. Incompatible architectures, missing files, and invalid uploads return clear validation errors instead of failing silently.
Last updated
Was this helpful?
Was this helpful?