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    Enables auto-configuration and validation of React components against a glassmorphic design token system using an AST correction engine. It supports managing UI presets, enforcing design uniformity in Monaco IDE, and exporting tokens as CSS, Tailwind, or JavaScript variables.
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    MIT
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    diagramzu-mcp lets an AI client (Claude, Cursor, ChatGPT, etc.) author Mermaid diagrams in a shared workspace that a team can read, comment on, embed, and present at a clean URL — rather than just generating a one-off diagram. Hosted endpoint https://mcp.diagramzu.ai/mcp or local npx -y @diagramzu/mcp. Also listed in the official MCP registry as ai.diagramzu/mcp.
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    A minimal MCP server for AI-driven canvas manipulation and visualization using tldraw. It enables AI clients to programmatically create, update, and manage shapes, flowcharts, and frames on a live interactive canvas.
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    Provides AI models with structured design guidelines and system prompts for creating consistent, high-quality interactive visualizations like charts, diagrams, and mockups. It enables on-demand loading of UI specifications to optimize token usage while ensuring visually polished and functional widget generation.
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    Enables direct interaction and control of SketchUp through Claude AI using the Model Context Protocol and a TCP socket connection. It allows for prompt-assisted 3D modeling, component manipulation, and the execution of arbitrary Ruby code within the SketchUp environment.
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    MIT
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    Enables creation, editing, and export of ASCII art diagrams using Monodraw on macOS, with tools for generating boxes, flowcharts, tables, trees, and sequence diagrams.
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    Enables AI agents to create, modify, and share diagrams on a live Excalidraw canvas through MCP tools, supporting shapes, text, arrows, batch operations, and export to shareable links with images.
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    MIT
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    Enables AI agents to read, write, and search local tldraw (.tldr) files, providing a persistent visual scratchpad for diagramming and note organization. It supports full CRUD operations on canvas shapes and metadata management for local canvas files.
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    Cloud infrastructure provisioning via natural language. Enables deploying production-ready infrastructure on AWS, GCP, Azure, or Oracle with a single prompt.
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    MIT