MCP server that adds vision capabilities to text-only AI models by sending images (local files, URLs, clipboard, screenshots) to a vision model and returning text descriptions.
Provides vision capabilities to text-only LLMs by analyzing image files via Qwen-VL and returning textual descriptions, with support for OCR, UI analysis, diagram/chart understanding, and code extraction through MCP stdio.
MCP server that provides a 'borrowed eye' for text-only LLMs, enabling them to identify and describe local images via the Qwen VL vision model, including face recognition, scene description, OCR, and targeted visual questioning.
An MCP server that enables any LLM to describe images from file paths, URLs, or base64 data by forwarding them to a supported vision provider such as OpenAI, Anthropic, or local Ollama models.
A desktop tray MCP server that gives text-only LLMs vision by sending images to a multimodal model (e.g., MiMo) and returning the answer, allowing MCP-compatible agents to analyze local images, URLs, or base64 data.
Enables text-only reasoning models to see images by wrapping vision-language models as MCP tools, supporting image description, OCR, chart analysis, and custom questioning within MCP-compatible IDEs.