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"A guide for improving AI prompt output quality" matching MCP servers:

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    πŸš€ Kill the Junior AI Era. πŸ€– Level up your AI code to Principal standards. No more sloppy lines or junior mistakes. Automated ESLint ✨ TypeScript πŸ”§ Prettier 🎨 SonarQube πŸ›‘οΈ Security πŸ”’ Complexity πŸ“Š in seconds. High-stakes quality, forced to ship only the best. βš‘πŸ† Goodbye, bad code. Hello, Principal Engineer. πŸš€βœ¨
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    MIT
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    Enables AI agents to screen and filter stock universe, compute custom quality scores, inspect score history, manage scoring systems, and generate shareable screen links, acting as the signed-in user.
    MIT
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    Enables AI agents to access and manage project guidelines, documentation, and context through a structured content system with template support and workflow management.
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    MIT
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    MCP server for managing and serving dynamic prompt templates using elegant and powerful text template engine. Create reusable, logic-driven prompts with variables, partials, and conditionals that can be served to any compatible MCP client like Claude Code, Claude Desktop, Gemini CLI, etc.
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    MIT
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    Provides MCP clients a single decision-only tool to classify prompts as safe for local or cloud models, or as containing PII or jailbreak content, without executing actions or calling AI models.
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    Cryptographic Autonomy 1.0 (Combined Work Exception)
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    Enables cleaning and sanitizing prompts through an LLM-powered tool that removes sensitive information, provides structured feedback with notes and risks, and normalizes prompt formatting. Supports configurable local or remote OpenAI-compatible APIs with automatic secret redaction.
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    MIT
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    Fix your vibe coding prompts before they reach the AI. Scores and rewrites across 4 dimensions β€” no API key, no server, just npx. Now with codebase-aware context injection for design, database, API, auth, testing, and state management.
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    MIT
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    Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.
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    MIT
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    MCP server providing 29 A-share analysis skills including real-time data, capital flow, limit-up tracking, technical/fundamental analysis, backtesting, risk control, and Xueqiu portfolio tracking, enabling AI agents to execute market research and strategy tasks.
    Apache 2.0
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    An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.
    14
    Apache 2.0