$ loading_
Enable AI assistants to query knowledge bases and generate grounded answers.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Modular RAG MCP Server" yet — see the docs or source repo.
Use query_knowledge_hub to search the product documentation collection for “access control” and summarize the key rules and caveats based on the results.
Relevant document snippets plus an accurate summary grounded in the retrieved results.
Call list_collections to list all available knowledge base collections and briefly explain what each collection is best used for.
A list of collections with a short description of each collection’s purpose.
Use get_document_summary to retrieve a summary of a technical design document, focusing on goals, key modules, and known limitations.
A clearly structured document summary that helps users quickly grasp the main points.
Turn unstructured documents into a searchable knowledge base for AI agents.
Expose modular retrieval and reasoning tools to AI assistants through MCP.
Query private knowledge bases with modular RAG, hybrid retrieval, reranking, and observability.
Build modular RAG workflows for document Q&A, semantic search, and knowledge bases.
Build and query vector knowledge bases for semantic search and RAG workflows.
Production-ready MCP server for query normalization, retrieval, and RAG prompt building.