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    An MCP server that enables Claude Code to generate images and short videos using Google's Gemini API (Imagen 4 for stills, Veo 3.1 for video). It integrates directly into development workflows, allowing AI assistants to create visual assets and reference them in code without context switching.
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    MIT
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    Enables AI agents to drive 360° cameras by connecting, checking status, reading and changing settings, taking photos, recording video, browsing the gallery, and downloading media as cancellable background jobs, with local stitching and export of 360° footage. It is honest about backend limits, returning structured, explained errors for anything a given camera or connection cannot do.
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    MIT
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    thicken turns photos of a real object into a GLB model at its real size and its metadata as JSON, read off the object by vision models and looked up in public catalogs. What it knows about each kind of object lives in a profile: a few come with thicken, and you can add your own.
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    652 npm
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    MIT
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    Enables Codex to draw pixel art and edit layers, animations, tilemaps, and palettes in an open Aseprite document on macOS, then export GIFs, PNG spritesheets, and editable Aseprite copies for game development.
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    MIT
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    Enables AI image generation, editing, and composition using Google's Gemini image models (Nano Banana Pro and Nano Banana). Supports text-to-image generation, multi-image composition, flexible aspect ratios, high-resolution output up to 4K, and real-time information grounding.
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    MCP server that captures short screen recordings as numbered, timestamped still frames and composes them into a single contact sheet returned as image content, letting AI agents reason about motion, animations, and UI transitions instead of inspecting video frame by frame. Also supports single screenshots and listing targetable windows.
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    Enables AI assistants to recognize and extract information from images via GLM-4V, supporting automatic screenshot recognition and MCP-based local image file reading for non-vision models like DeepSeek.
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    Enables coding agents to examine a rendered web page by cross-checking what the browser reports about the DOM/CSS against what is actually painted in pixels, pinpointing which element is broken and the evidence why. Reports visual problems without requiring a baseline, and is designed to grow into design-token extraction and accessibility/UX audits built on Playwright.
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    MIT
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    Enables web content extraction, screenshot capture, web search, arXiv paper search, and image search through Jina AI's APIs. Provides tools for reading URLs as markdown, searching the web for current information, and finding academic papers or images.
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    Apache 2.0
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    Enables AI assistants to procedurally generate, edit, quantize, and export 2D retro pixel art textures and tilesets for game development, with built-in palettes, dithering, and pixel-level manipulation tools.
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    MIT
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    Analyzes webpage screenshots to extract precise layout information by locating image assets and calculating spatial relationships, enabling AI assistants to accurately recreate layouts with proper semantic structure using computer vision.
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    MIT
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    Enables web searching via SearXNG, page content extraction with Crawl4AI, and image analysis using vision language models. It provides AI agents with tools for information synthesis and web-based data retrieval through OpenAI-compatible LLM endpoints.
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    Apache 2.0
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    Enables local, upload-free analysis of publicly viewable videos through tools that pull metadata, chapter plans, platform subtitles or speech-to-text transcripts, sampled frames and contact sheets, 527-class sound event tags, and comment analysis. It downloads only the minimum necessary bytes, so users can inspect long videos section by section, job-poll lengthy runs, and check the local model/environment setup without sending media to any cloud service.
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    MIT