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MCP Server for Computer Vision
MCPOpen SourceGPL-3.025.8
by MRonaldo-gif • Analytics & Monitoring
An MCP server for image object detection, segmentation, and pose estimation using Ultralytics models.
Example Use Cases
- 1
Perform image object detection using YOLO models
- 2
Segment objects and images with cutting-edge techniques
- 3
Estimate human poses in images for application development
Description
This repository provides a Python server implementing the Model Context Protocol (MCP) for performing computer vision tasks such as object detection, image segmentation, and pose estimation. It utilizes YOLOv8 and YOLOv10 models for processing images locally or via network inputs. Ideal for enhancing computer vision applications with robust detection, segmentation, and pose estimation capabilities.
Capabilities(5 total)
Tools (4)
add
Add two numbers together. Args: a: First number b: Second number Returns: The sum of a and b
a:number*b:number*
subtract
Subtract the second number from the first. Args: a: Number to subtract from b: Number to subtract Returns: The result of a - b
a:number*b:number*
multiply
Multiply two numbers together. Args: a: First number b: Second number Returns: The product of a and b
a:number*b:number*
divide
Divide the first number by the second. Args: a: Numerator b: Denominator Returns: The result of a / b
a:number*b:number*
Resources (1)
calculator_help
Basic calculator help information.
URI: calculator://helpMIME: text/plain
Quick Actions
Security
Scanned 2 month(s) agoRisk Level
MINIMAL
Read-only data retrieval, no side effects
Trust Score
C58/100
9/17 checks passed
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Quick Stats
Service TypeMCP
Pricing ModelFree
Capabilities4 Tools / 0 Prompts / 1 Resources
OwnerMRonaldo-gif
CategoryAnalytics & Monitoring
DependenciesStandalone
Tags
Computer visionObject detectionImage segmentationPose estimationAI inference