An MCP server that provides tools to load and fetch documentation from any llms.txt source, giving users full control over context retrieval for LLMs in IDE agents and applications.
An MCP server that enables users to fetch and audit documentation from user-defined llms.txt index files. It provides tools to list documentation sources and retrieve content from specific URLs with built-in domain access controls for secure context retrieval.
A project-agnostic MCP server that exposes Markdown documentation from a project's /docs folder as MCP resources for AI agents. It provides stable, up-to-date context to reduce hallucinations and ensure agents remain aligned with project-specific conventions and goals.
A lightweight, zero-config MCP server that makes documentation and API specifications instantly accessible to AI models using the llms.txt standard. It enables searching and retrieving full documentation, OpenAPI, and AsyncAPI specs without requiring a complex RAG infrastructure or vector database.