Provides controlled access to llms.txt documentation files through MCP tools, allowing AI assistants to fetch and read documentation from user-approved domains with full audit visibility of tool calls and context retrieval.
Auto-discovers llms.txt documentation from project dependencies and exposes it to AI coding agents via MCP, enabling agents to read first-party docs without scraping or guessing.
Enables MCP host applications to retrieve and process structured documentation from user-defined llms.txt files. It provides tools to fetch specific URLs and audit the documentation context returned to the LLM.
Aggregates documentation from multiple sources (llms.txt format or web scraping) and provides semantic search capabilities using vector embeddings and hybrid search for each documentation source.
Provides a user-defined list of llms.txt files and a fetch_docs tool to read documentation URLs from those files, enabling controlled and auditable documentation retrieval for MCP host applications.
