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    Enables AI assistants and developers to analyze code for language-specific best practices and idiomatic patterns across programming languages, CI automation, and configuration formats.
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    MIT
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    Exposes your organization's Terraform style guide to AI coding agents, enabling them to generate, validate, and ensure Infrastructure as Code follows your specific conventions, naming standards, security defaults, and best practices.
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    MIT
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    Enables static security audit of Solidity smart contracts by analyzing source code or deployed bytecode for vulnerabilities, providing risk scores and detailed findings.
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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.
    14
    MIT
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    Enables AI-assisted X++ development for Dynamics 365 Finance and Operations by pre-indexing the entire codebase and providing 54 specialized tools for metadata lookup, code generation, and best practice validation.
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    MIT
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    Provides coding agents with a mental map of codebases via progressive disclosure, enabling efficient exploration of project structure and entity relationships.
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    GPL 3.0
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    Enables AI-assisted FlutterFlow development by reading, exploring, and understanding FlutterFlow projects through Claude and other MCP-compatible clients.
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    MIT
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    Provides read-only, structurally safe introspection of a Laravel codebase, letting AI agents inspect routes, models, migrations, jobs, and config without risk of mutation or secret disclosure.
    8
    MIT
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    MCP server for IFS Cloud PL/SQL unit testing, enabling check of testability, generation of unit tests, and orchestration of deploy/run steps via ifs-f1-codegen-dev.
    6
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    SourceSage is an MCP (Model Context Protocol) server that efficiently memorizes key aspects of a codebase—logic, style, and standards—while allowing dynamic updates and fast retrieval. It's designed to be language-agnostic, leveraging the LLM's understanding of code across multiple languages.
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    Enables automatic generation of explicit boilerplate methods (getter/setter/equals/hashCode/toString/constructors) for Java entity classes, replacing Lombok dependencies with visible, reviewable code.
    MIT