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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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    Extracts deterministic architecture maps from codebases for AI agents, enabling queries about blast radius, routes, security findings, and production readiness without sending code anywhere.
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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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    MCP server that creates, edits and exports architecture diagrams as .fluyo.json files, operating through tools like create_diagram, edit_diagram, and export_diagram directly from Claude.
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    MIT
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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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    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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    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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    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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    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