Enables non-vision LLMs to understand images, extract text via OCR, and parse documents through a unified MCP interface, with local-first processing and optional OpenAI-compatible channels.
MCP server that enables LLMs to understand images without native vision by converting image regions into text encodings (ASCII art, grayscale grids, color stats) and supporting progressive zoom, OCR, and overview summaries. Users can load images, get chunk overviews, crop and encode specific regions, and extract text using normalized coordinates.
Enables text-only models to understand images through a conversational MCP server, supporting multi-turn follow-ups, URL inputs, and OpenAI-compatible vision APIs.
Zero-dependency MCP server that enables text-only models to "see" images via a read_image tool, which forwards the image (local path, URL, data URL, or base64) to any OpenAI-compatible vision API and returns the textual description to the main model.