RAG Documentation Server

Example Use Cases

• 1

  Search and retrieve relevant documentation excerpts using natural language queries to augment responses.

• 2

  Crawl and index web documentation automatically and keep a queue of pages to process.

• 3

  Manage documentation sources (list, remove) and embed documentation context into LLM prompts via vector search.

Description

This MCP server processes and indexes documentation from multiple sources into a vector database, enabling semantic search and retrieval of relevant excerpts. It provides tools to crawl pages, manage a processing queue, run indexing, and remove or list stored sources. The server is intended to augment AI assistants with contextual documentation during responses and supports real-time context augmentation for LLMs.