MCP YOLOE: Zero-Shot Object Detection & Segmentation

Name: MCP YOLOE: Zero-Shot Object Detection & Segmentation
Author: rjn32s

@rjn32s

关于 MCP YOLOE: Zero-Shot Object Detection & Segmentation

Provide your AI agents with "eyes." This server enables open-vocabulary object detection and instance segmentation using naturally phrased text prompts (e.g., "detect the laptop next to the coffee").

#vision #ai #object #detection #segmentation #zero-shot #yolo

基本信息

分类

其他

传输方式

stdio

发布者

rjn32s

提交者

Rajan shukla

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-yolo": {
      "command": "uvx",
      "args": [
        "mcp-yolo"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is MCP YOLOE: Zero-Shot Object Detection & Segmentation?

MCP YOLOE is a Model Context Protocol server that gives AI agents advanced computer vision using zero-shot learning. It detects and segments any object described in natural language, unlike fixed-list YOLO models.

How to use MCP YOLOE: Zero-Shot Object Detection & Segmentation?

You interact through an AI agent (e.g., Claude) by providing a natural language prompt such as “Find the ‘vintage typewriter’ in this image and give me its exact coordinates.” The server accepts local file paths, remote image URLs, and Base64-encoded images as input.

Key features of MCP YOLOE: Zero-Shot Object Detection & Segmentation

Zero-shot detection with natural language prompts.
Precision segmentation with exact polygon masks.
Flexible inputs: local paths, URLs, Base64.
Agent-first design for Claude, IDEs, and workspace agents.
Uses YOLOE26‑L architecture (55.0 mAP, ~6.2ms on T4).

Use cases of MCP YOLOE: Zero-Shot Object Detection & Segmentation

Find and locate arbitrary objects in images using descriptive text.
Obtain exact polygon masks for detected objects for further processing.
Integrate computer vision capabilities into AI agents for automated image analysis.
Support diverse input sources (local files, URLs, embedded data) in agent workflows.