Creates a local database of indexed technical documentation from web crawls and local files, enabling AI agents to efficiently search and retrieve documentation through MCP tools.
A documentation MCP server that crawls websites and Git repositories, stores them as Markdown, and provides tools to search and retrieve documentation for local LLMs and AI agents.
Local documentation search server for AI models using hybrid retrieval (phrase, keyword, vector). Provides MCP tools to search and fetch documentation from bundled or custom doc sets without any external API keys.
Indexes documentation sites by base URL and serves keyword search, optional semantic search, and Markdown page retrieval as MCP tools, all from a single SQLite file.
Provides tools for ingesting documents into a local vector database and retrieving relevant information via semantic search, enabling retrieval-augmented generation for MCP clients.
Scrapes documentation sites, chunks and embeds content locally, then retrieves relevant passages for queries. Enables agents to ask questions grounded in documentation.