YOLOSAFE

A powerful YOLO (You Only Look Once) computer vision service that integrates with Claude AI through Model Context Protocol (MCP). This service enables Claude to perform object detection, segmentation, classification, and real-time camera analysis using state-of-the-art YOLO models.

Features

• Object detection, segmentation, classification, and pose estimation
• Real-time camera integration for live object detection
• Support for model training, validation, and export
• Comprehensive image analysis combining multiple models
• Support for both file paths and base64-encoded images
• Seamless integration with Claude AI

Setup Instructions

Prerequisites

• Python 3.10 or higher
• Git (optional, for cloning the repository)

Environment Setup

1. Create a directory for the project and navigate to it:

mkdir yolo-mcp-service
cd yolo-mcp-service

1. Download the project files or clone from repository:

# If you have the files, copy them to this directory
# If using git:
git clone https://github.com/GongRzhe/YOLO-MCP-Server.git .

1. Create a virtual environment:

# On Windows
python -m venv .venv

# On macOS/Linux
python3 -m venv .venv

1. Activate the virtual environment:

# On Windows
.venv\Scripts\activate

# On macOS/Linux
source .venv/bin/activate

1. Run the setup script:

python setup.py

The setup script will:

• Check your Python version
• Create a virtual environment (if not already created)
• Install required dependencies
• Generate an MCP configuration file (mcp-config.json)
• Output configuration information for different MCP clients including Claude

1. Note the output from the setup script, which will look similar to:

MCP configuration has been written to: /path/to/mcp-config.json

MCP configuration for