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 local MCP server that gives LLMs eyes for images by performing object detection (YOLOv8) and text recognition (EasyOCR), outputting descriptive statements about objects and text positions without any API key or cloud dependency.
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.
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.
MCP server that provides visual question answering, image description, object detection, OCR, and image manipulation tools using OpenAI-compatible vision models.
Zero-dependency MCP server that equips text-only LLMs (e.g., DeepSeek) with vision by converting images to text descriptions via OpenAI-compatible vision APIs, exposing an img2text tool with multi-provider fallback.