This is an MCP server that connects to the Tuba.ai platform, allowing you to control and interact with AI vision workflows programmatically, providing functions such as execution, monitoring, configuration, and file upload.

MCP OpenVision is an image analysis server based on OpenRouter's vision models, providing image analysis capabilities for AI assistants.

A computer vision server implemented based on Ultralytics and the MCP protocol, supporting functions such as object detection, image segmentation, and pose estimation

MCP Vision Relay is an MCP server that provides image analysis capabilities for MCP clients that only support text, such as Claude and Codex, by encapsulating locally installed Gemini and Qwen command - line tools, enabling them to process pictures in local paths, URLs, or base64 - encoded format.

An MCP service for YouTube video analysis based on the Google Gemini Vision API, providing functions such as video description, summarization, Q&A, and key segment extraction.

The YOLO MCP Service is a powerful computer vision service that integrates with Claude AI through the Model Context Protocol (MCP), providing functions such as object detection, segmentation, classification, and real-time camera analysis.

The Moondream MCP Server is a powerful model context protocol server that provides advanced image analysis functions for applications through the Moondream vision model and seamlessly integrates with Claude and Cline.

A web screenshot tool optimized for AI vision workflows. Automatically segments the entire web page into 1072x1072 pixel tiles to ensure the best processing effect. Supports MCP integration and screen recording functions

An AI vision analysis MCP server based on Google Gemini and Vertex AI, supporting multimodal analysis of images and videos, providing functions such as object detection and image comparison, and can be integrated into various MCP clients.

The Orion Vision MCP Server is an open - source project based on the Model Context Protocol (MCP), providing seamless integration with Azure Document Intelligence services and supporting analysis and data extraction functions for multiple document types.

ScreenMonitorMCP is a revolutionary AI vision server project that provides real-time screen monitoring, visual analysis, and intelligent interaction capabilities for AI assistants such as Claude, enabling AI to 'see' and operate the user's screen.

Android-MCP is a lightweight open-source project that serves as a bridge between AI agents and Android devices. It enables real-world task operations such as app navigation, UI interaction, and automated testing through the MCP server, without relying on traditional computer vision or pre-set scripts.

MCP Hub is a framework for creating and managing Model Context Protocol (MCP) servers and clients, integrating the UV tool to simplify package management and configuration. The project includes AI - related computer vision scripts and dataset processing tools, supporting rapid deployment and development.

The OpenCV MCP Server is a Python - based computer vision service that provides OpenCV's image and video processing capabilities through the Model Context Protocol (MCP). It offers a full set of computer vision tools from basic image processing to advanced object detection for AI assistants and language models, including image processing, edge detection, face recognition, video analysis, and real - time object tracking.

A web page screenshot tool optimized for AI vision workflows, automatically splitting into 1072x1072 pixels to meet the processing requirements of the Claude Vision API

MCP-hfspace is a server tool that simplifies the connection to Hugging Face Spaces. It supports multiple AI functions such as image generation, speech processing, and vision models, and seamlessly integrates with Claude Desktop.

An image recognition server based on the Model Context Protocol that provides image analysis and description functions through OpenAI-compatible vision models, supporting cloud and local model integration.

The official website of A2A-MCP showcases the technical vision, core advantages, and application scenarios of the multi-agent collaboration protocol, and is built using a modern front-end technology stack.

Azure AI Vision Face Liveness Detection MCP Server for embedding proof of existence in Agentic AI workflows.

A complete Groq MCP Server project that serves as an intelligent bridge to connect applications with the Groq API, supports multiple AI models (text, audio, vision, batch processing), and has advanced functions such as intelligent routing, rate limiting, and cache optimization.