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io.github.rjn32s/mcp-yolo

Official

by rjn32s · Python

An MCP server providing zero-shot object detection and segmentation using Ultralytics YOLOE.

MCP-YOLO (io.github.rjn32s/mcp-yolo)

MCP-YOLO is a Model Context Protocol (MCP) server that provides zero-shot object detection and segmentation. It is powered by Ultralytics YOLOE and is described as an “agent-first development platform” for developers and AI agents to perform detection and segmentation.

🛠️ Key Features

  • MCP server interface for model context integration
  • Zero-shot object detection
  • Zero-shot object segmentation
  • Ultralytics YOLOE as the underlying engine

🚀 Use Cases

  • Object detection for AI agents without explicit training per category
  • Object segmentation for image understanding tasks via an MCP-connected workflow

⚡ Developer Benefits

  • Enables developers to connect detection and segmentation capabilities through MCP
  • Uses Ultralytics YOLOE to support the server’s detection/segmentation behavior

⚠️ Limitations

  • The available description does not specify supported input types, model configuration options, or output formats beyond detection and segmentation