Reverse-engineers design videos and images into structured frontend implementation specifications using vision LLMs and FFMPEG for frame-level analysis.
Provides Claude with detailed image inspection capabilities, including metadata extraction, histogram analysis, tonal and color analysis, sharpness detection, and more, supporting both standard and RAW formats.
A streamlined MCP server for XMP metadata embedding with beautiful formatting and smart filename indicators, enabling metadata embedding, reading, validation, and report generation for lifestyle, product, and orbit schemas.
Enables intelligent analysis and organization of image collections with smart filename generation, metadata extraction, and automated folder organization. Supports batch processing, color analysis, EXIF data extraction, and multiple naming styles for efficient photo management.
Enables AI assistants to locally process images with tools for cropping, zooming, enhancement, edge detection, segmentation, and text region extraction, all without external API keys. It uses PIL, OpenCV, and scikit-image for robust image analysis.
MCP server for MarkItUp's AI image-annotation pipeline. Generate polished marketing-visual variations of any screenshot, regenerate, AI outpaint, and remove backgrounds —
powered by Claude analysis + Gemini rendering.
A server that accepts image URLs and analyzes their content using GPT-4-turbo, enabling Claude AI assistants to understand and describe images through natural language.
A FastAPI-based server that provides a web UI for uploading, processing, and analyzing trading screenshots with automatic trade data extraction and analytics.
Enables text-only agents to process images by accepting image files, base64 data, or URLs, sending them to multimodal models, and returning structured text results via MCP.
MCP server that lets AI assistants like Claude or Cursor extract structured data (e.g., invoices) from images and PDFs via Vision API, with tools for analysis, questions, and preset management.
An MCP server that uses Xiaomi MiMo v2.5 multimodal model to provide image recognition capabilities (description, multi-image analysis, OCR, and image info validation) for text-only main models like deepseek-v4-flash, accepting local paths, URLs, file://, and base64 data inputs.
Enables analysis of an image's optical properties (color temperature, light vectors, luminance dynamics) and generation of physically grounded relighting variants, harmonized composites with contact shadows, and calibrated diffusion prompts for GPT Image and Nano Banana targets.