Enables an AI assistant to batch-drive ArmorPaint headlessly via its native CLI and scripting engine, re-exporting projects at different presets and building procedural materials without opening the GUI.
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.
Reverse-engineers design videos and images into structured frontend implementation specifications using vision LLMs and FFMPEG for frame-level analysis.
Enables local OCR transcription of images using tesseract.js, with optional low-token AI-generated descriptions, folder batch processing, and compatibility with MCP clients like ChatGPT, Claude, opencode, and Cursor.
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.
Privacy-first MCP server for macOS that allows AI agents to search local images using natural language descriptions, leveraging MLX CLIP embeddings and LanceDB for fast, fully offline search.
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 natural language search of local photo archives using AI-powered semantic understanding, with integration into Claude Desktop via the Model Context Protocol.
An MCP server that searches the web for images, creates a numbered contact sheet for visual selection, and downloads the chosen images with provenance metadata. Works without an API key.
Enables interaction with Figma designs through the Figma API, allowing users to export images in multiple formats, extract style data and CSS, analyze design elements, and retrieve SVG code from Figma files. Supports batch operations and comprehensive design element analysis including images, vectors, and components.
Enables AI assistants to access and control network cameras to capture images and perform analysis including brightness detection, color distribution, and edge detection.
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.