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    Offline MCP server for SAP ABAP static analysis, ABAP Cloud readiness scoring, and RAP scaffolding. It enables AI agents to lint ABAP source, compare reworks, check released APIs, and generate RAP business objects without needing an SAP system.
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    MIT
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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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    Enables analysis of any GitHub repository to get architecture, file roles, execution flows, system design Q\&A, and structured agent context. Works with MCP-compatible clients like Claude Desktop, Cursor, and Windsurf.
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    MIT
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    The Diagrams.so MCP server enables generating, editing, and managing cloud architecture diagrams from any MCP client, wrapping the public Diagrams.so API.
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    Apache 2.0
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    Exposes ASCIIFlow drawing primitives as tools to enable AI assistants to generate ASCII wireframes and diagrams from natural language descriptions. It provides commands for creating canvases and drawing boxes, lines, arrows, and text using a character-grid coordinate system.
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    A comprehensive bridge connecting AI agents to Unreal Engine 5.7 through 39 MCP tools for scene manipulation, asset management, and blueprint control. It enables real-time perception and editor automation using the Remote Control API and file-based protocols.
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    MIT
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    Score your agent's governance (0-100), lint MCP tool definitions, and estimate costs across all major models. Free diagnostic tools with no API key needed. Expert skill files on governance, economics, and system architecture available with free tier.
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    MIT
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    A specialized architecture design MCP server that enables AI-assisted developers to plan optimal system structures through interactive consultations. It generates structured ARCHITECTURE.md and .ai-context.yaml files to guide AI coding tools in building scalable and cost-effective infrastructure.
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    MIT
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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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    MIT
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    Enables AI assistants to programmatically create, read, validate, and modify Stella system dynamics models in the XMILE format. It supports building complex stock-and-flow diagrams and exporting them as .stmx files for use in Stella Professional.
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    Enables LLMs to work with the Optics Design System, providing access to 83 design tokens (HSL-based colors, spacing, typography), 24 components with dependencies, and tools for theme generation, accessibility checking, and code scaffolding.
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    MIT
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    Integrates Archaic's AI-powered architecture analysis with Claude Code, enabling interactive exploration of component connections, data flows, and system structure through natural language.
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    MIT