Enables LLMs to see clipboard screenshots without saving files, using free Grok visual models, and integrates seamlessly with Command Code, Cursor, Claude, and other coding agents.
Enables text-only models to understand images by intercepting pasted images, saving them locally, and using a vision MCP server to analyze them with multimodal backends like Qwen-VL, Doubao, or GLM-4V.
Gives text-only LLM coding agents vision by routing images to a multimodal model and returning detailed textual descriptions. Supports local files, URLs, clipboard, base64, raw bytes, and multiple providers like OpenAI, Anthropic, and Gemini.
Provides image understanding capabilities to coding models without vision support by automatically invoking a vision model and returning text descriptions, enabling seamless context-aware coding with images.