Libragen is a tool designed to enhance the accuracy of AI coding agents by providing them with up-to-date, authoritative documentation. It enables users to create private, local Retrieval-Augmented Generation (RAG) libraries that function offline, eliminating the need for API keys or cloud services. These libraries can be shared as single files, ensuring that entire teams have consistent and current information. By grounding AI tools in the latest documentation, Libragen significantly reduces instances of AI hallucinations, where coding agents might suggest deprecated methods or non-existent functions due to outdated training data. Key Features and Functionality: - Hybrid Search: Combines vector similarity with BM25 keyword search using reciprocal rank fusion to deliver the most relevant documentation results. - MCP Compatibility: Offers first-class support for the Model Context Protocol, ensuring seamless integration with tools like Claude, Cursor, VS Code, Windsurf, and other MCP-compatible clients. - Portability: Generates complete libraries as single `.libragen` files, facilitating easy sharing via email, version control systems, or other methods, all while functioning offline without the need for user accounts. - Privacy and Offline Operation: Operates entirely on the user's machine, ensuring that proprietary documentation remains private without reliance on third-party services. - Collections: Allows users to curate and distribute bundles of useful libraries to their teams, which can be installed with a single command. - CLI and TypeScript API: Provides a command-line interface and a comprehensive TypeScript API for building and querying libraries, enabling integration into various tools and workflows. Primary Value and User Solutions: Libragen addresses the challenge of AI coding agents working with outdated or incomplete context by providing them with current and authoritative documentation. This approach reduces the likelihood of AI hallucinations, where agents might suggest incorrect or deprecated code. By enabling the creation of private, local RAG libraries that function offline, Libragen ensures that teams can maintain control over their documentation without the need for cloud services or external dependencies. This solution is particularly beneficial for organizations seeking to enhance the reliability of their AI tools while maintaining data privacy and minimizing operational complexity.