"MUI" matching MCP servers:

Exposes local Umi-OCR v2 capabilities to AI agents via MCP, enabling image text extraction, batch OCR, PDF OCR, and status checks without manually starting the service.

Exposes a shared video-editing timeline as MCP tools, letting Claude Code, Codex or any MCP client cut, trim, layer, caption, mix and generate motion graphics on the same versioned project the browser editor has open. Every edit an agent makes shows up live, is labelled with its author, and can be undone.

Enables comparison of mobile app screenshots against design mockups, with Calorix as the first integration target.

Enables AI agents to read social media and article links that return no useful HTML, returning transcripts, on-screen text, image OCR, captions, metadata, and optional viral breakdowns with verbatim-checked quotes or translations. Works with Xiaohongshu, Douyin, TikTok, YouTube, X, and ordinary web pages through a hosted remote endpoint, with a Python SDK, CLI, and stdio bridge for clients that need them.

MCP server for ingesting UI screenshots, Figma MCP node JSON, or hybrid Figma-plus-screenshot sources into a cross-platform design-to-code artifact pipeline.

Enables generating images, videos, characters, and scenes through Google Flow. Supports SSE and Vercel deployment for integration with Gemini Spark and other IDEs.

Enables ChatGPT users to search and browse a private photo library, inspect metadata, and receive real image previews through read-only tools, while keeping encrypted sessions server-side.

Enables AI agents to generate professional storyboards and videos from scripts or creative descriptions via MCP-compatible clients.

Analyzes app screenshots to identify UI/UX issues, compare designs with implementations, and provide actionable fixes using GPT-4o/GPT-5.2 vision capabilities. Supports single/batch analysis, design comparison, and automated report generation for iOS, Android, web, and desktop platforms.

Enables a connected LLM to inspect brain MRI slices as crops and montages with coordinates, compare a region against its mirrored hemisphere, and review the pipeline's candidate hotspots. It lets the model write prioritised "area to review" annotations that appear live in the browser viewer, and move or read the clinician's crosshair position.

Enables discovery of ComfyUI nodes and building/managing workflows with real-time execution via WebSocket. Provides 50+ tools for node discovery, workflow building, template usage, model management, and batch/chain execution.

Enables automated visual testing by comparing screenshots against baseline images using OpenAI to verify UI consistency. It generates detailed performance reports in both terminal and Excel formats based on provided user stories and acceptance criteria.