mcp-ragdocs
The RAG Documentation MCP Server is a tool designed to enhance AI assistants with relevant documentation context through vector-based semantic search. It supports multiple documentation sources and provides features for automated processing and real-time augmentation of AI responses.
What is the primary use of the RAG Documentation MCP Server?
The primary use is to enhance AI responses by providing relevant documentation context through vector search, making AI systems more informative and context-aware.
How does the server support multiple documentation sources?
The server can index and search through various documentation sources, allowing it to provide comprehensive and relevant information from multiple origins.
What is the role of semantic search in this server?
Semantic search allows the server to understand and process natural language queries, providing more accurate and contextually relevant search results.
Can I remove documentation sources once they are added?
Yes, you can permanently remove specific documentation sources from the system using the remove_documentation tool.
What happens if there is an error during the queue processing?
The run_queue tool includes proper error handling and retry logic to manage errors during the processing of URLs in the queue.