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Srag addresses the common limitation of AI coding assistants by enabling them to understand and leverage your specific codebase, patterns, and conventions. By indexing all your repositories, srag allows AI assistants to perform semantic searches, providing instant access to relevant implementations, patterns, and architectural context. This integration not only helps in reusing existing code and maintaining consistent style but also enhances debugging, onboarding, and cross-project knowledge transfer, ultimately leading to more accurate code suggestions and reduced token usage through its Model Context Protocol (MCP) server.