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    AI 規格大師 — MCP server bridging specs (Linear / JIRA / GitHub Issues / Notion / Markdown / Figma) to tests, with bidirectional traceability and a spec-quality coach. Sibling to mk-qa-master.
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    Automates the evaluation of GitHub hackathon submissions by providing tools to collect issue data, apply scoring rubrics, and generate ranking reports. It enables a multi-agent system to manage scoring consistency, statistical outlier detection, and feedback generation through the GitHub CLI.
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    Lightweight Node.js dependency vulnerability audit tool with CLI and MCP Server modes. Supports npm/pnpm, full dependency chain tracing, remote GitHub repo auditing, and generates Markdown/HTML reports.
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    A Node.js-based frontend security audit tool that performs comprehensive dependency security audits for both local projects and remote repositories. Generates detailed Markdown reports with vulnerability detection, risk assessment, and fix recommendations.
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    Automates the conversion of Figma designs into TypeScript React components and integrates with GitHub to create pull requests for the generated code. It includes visual regression testing with Playwright and accessibility validation to ensure implementations match the original designs.
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    Python MCP server for Selenium WebDriver — 84 tools for browser automation, element interactions, assertions, self-healing locators, and codegen for Java TestNG / JUnit 5 / Cucumber / pytest / C# NUnit / Playwright and CI pipelines (GitHub Actions / Jenkins / GitLab CI). No ChromeDriver setup needed.
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    Allows AI assistants such as Cursor/Cline/GitHub Copilot to use Google's lighthouse tool to measure perf metrics for your webpage. You can then run an agentic loop and get the assistants to optimize those metrics!
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    Enables comprehensive GitHub PR reviews through Cursor's AI by fetching PR diffs, running static analysis tools (ESLint, Prettier, TypeScript, Semgrep), executing tests, and generating detailed code review reports with inline comments.
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    Enables access to Codacy's code quality platform through natural language, providing repository management, security analysis, pull request reviews, and local CLI-based code analysis. Supports comprehensive code quality monitoring including issues, coverage, security vulnerabilities, and technical debt assessment across organizations and repositories.
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    A frontend security dependency auditing tool that identifies vulnerabilities in local and remote repositories using the Model Context Protocol. It provides detailed audit information like CVSS scores and dependency chains, generating standardized markdown reports.
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    Enables AI agents to scan GitHub repositories for security vulnerabilities, deployment blockers, and code quality issues. It provides detailed findings and auto-generated code patches to help developers ensure their code is production-ready.
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    MIT