Adds vision capabilities to text-only LLMs by integrating external vision models via MCP. It supports OCR, error screenshot reading, UI description, image comparison, and natural-language queries on images.
Local vision-capable MCP server that lets AI agents describe screenshots, UI, charts, and photos via vision and OCR tools, with support for multiple providers and automatic fallback.
Multi-backend AI vision for MCP agents. Analyze images, screenshots, and documents using local Ollama models or cloud APIs like OpenAI, Google Gemini, and OpenRouter.
Vision MCP enables text-only agents to understand images through any OpenAI-compatible vision model. It supports local images, URLs, screenshots, documents, charts, and code errors with tools like analyze_image and understand_image.
Bridges vision models to text-only coding models using Florence-2, enabling non-vision LLMs to describe images, extract text, and analyze screenshots via MCP tools.
