10 boosters for "augment" — AI-graded, open source, ready to install
RagCode MCP is a semantic code navigation tool that integrates RAG-powered code search into Windsurf and other IDEs, enabling developers to intelligently query and understand multi-language codebases using local LLMs. It's ideal for developers working with Laravel, Go, Python, and PHP who need fast, context-aware code exploration without leaving their IDE.
A recursive RAG (Retrieval-Augmented Generation) MCP server that integrates with Cursor IDE to enable intelligent code retrieval and context optimization through vector embeddings and a rules optimizer. Developers using Cursor can leverage this to enhance code understanding, documentation retrieval, and AI-assisted development workflows.
A Cursor-integrated ruleset that enforces React best practices and modern patterns for Next.js applications, helping developers write cleaner, more maintainable component code.
TheiaChat CLI Copilot Instructions is a comprehensive governance framework for an AI-assisted TypeScript terminal tool, designed to enforce enterprise-grade code quality, security, and architectural rigor through mandatory PRD-first workflows and triple-check verification gates. Enterprise teams and AI coding agents working on TypeScript CLI projects benefit from its structured approach to secure, validated feature development.
An MCP server that integrates local system capabilities with Augment AI, enabling Claude Desktop and Claude Code to access system-level operations through the Model Context Protocol. Ideal for developers seeking to extend Claude's capabilities with local machine access.
A production-grade system prompt for building a security-hardened RAG (Retrieval-Augmented Generation) document Q&A platform with JWT auth, multi-tenant isolation, and Gemini integration. Ideal for teams building enterprise-ready AI assistants that prioritize security and observability.
Copilot Instructions that optimize AI context loading for the ai-augmented-project-template repository by providing query scripts and decision trees to reduce token usage by 85-95%. Developers working with GitHub Copilot on this project benefit from faster, more efficient AI-assisted development.
This booster provides Copilot instructions for a Node.js RAG (Retrieval-Augmented Generation) customer support system, helping developers integrate intelligent document-based chat functionality with best practices for async/await, logging, and error handling.
An MCP server that enables semantic code search and API reference lookup for the Immersive Web SDK (WebXR) using RAG with vector embeddings, allowing Claude to intelligently retrieve and reference XR development resources.
A lightweight production-ready RAG system prompt that integrates contextual chunking and vector retrieval via Chroma, designed for developers building AI-enhanced code editors and IDEs. Developers working with Claude, ChatGPT, or Cursor who need retrieval-augmented generation without heavy infrastructure will benefit from this ready-to-deploy foundation.
