Official descriptionRAG Documentation MCP Server An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.
Config template (adjust for your client)
claude mcp add mcp-ragdocs -- npx -y mcp-ragdocs
A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.
Star count
265 โ ยท hannesrudolph/mcp-ragdocs ยท read from the repository page ยท (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list ยท type: MCP server
Harvest history
first seen 2026-10-09 ยท last seen 2026-10-16 ยท seen 32ร ยท listed by 10 sources
Score
score 1,003 ยท 265 โ ยท 10 sources ยท mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP ๆๅก. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository hannesrudolph/mcp-ragdocs๏ผfirst catalogued 2026-10-09๏ผlast seen 2026-10-16ใThere is no official certification or quality rating here โ we record sources and dates only.
An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context. Features - Vector-based documentation search and retrieval - Support for multiple documentation sources - Semantic search capabilities - Automated documentation processing - Real-time context augmentation for LLMs Tools search_documentation Search through stored documentation using natural language queries. Returns matching excerpts with context, ranked by relevance. **Inputs:** - query (string): The text to search for in the documentation. Can be a natural language query, specific terms, or code snippets. - limit (number, optional): Maximum number of results to return (1-20, default: 5). Higher limits provide more comprehensive results but may take longer to process. list_sources List all documentation sources currently stored in the system. Returns a comprehensive list of all indexed documentation including source URLs, titles, and last update times. Use this to understand what documentation is available for searching or to verify if specific sources have been indexed. extract_urls Extract and analyze all URLs from a given web page. This tool crawls the specified webpage, identifies all hyperlinks, and optionally adds them to the processing queue. **Inputs:** - url (string): The complete URL of the webpage to analyze (must include protocol, e.g., https://). The page must be publicly accessible. - add_to_queue (boolean, optional): If true, automatically add extracted URLs to the processing queue for later indexing. Use with caution on large sites to avoid excessive queuing. remove_documentation Remove specific documentation sources from the system by their URLs. The removal is permanent and will affect future search results. **Inputs:** - urls (string[]): Array of URLs to remove from the database. Each URL must exactly match the URL used when the documentation was added. list_queue List all URLs currently waiting in the documentation processing queue. Shows pending documentation sources that will be processed when run_queue is called. Use this to monitor queue status, verify URLs were added correctly, or check processing backlog. run_queue Process and index all URLs currently in the documentation queue. Each URL is processed sequentially, with proper error handling and retry logic. Progress updates are provided as processing occurs. Long-running operations will process until the queue is empty or an unrecoverable error occurs. clear_queue Remove all pending URLs from the documentation processing queue. Use this to reset the queue when you want to start fresh, remove unwanted URLs, or cancel pending processing. This operation is immediate and permanent - URLs will need to be re-added if you want to process them later.