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Enable AI assistants to search, summarize, and use RAG knowledge bases via MCP.
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 Modular RAG MCP Server's query_knowledge_hub to search for “evaluation methods for enterprise private RAG systems” and return key findings, cited sources, and related documents.
A hybrid search result with an answer summary, source citations, and related document details.
Call list_collections to list all current knowledge base collections, and explain which are suitable for product documentation Q&A versus research material retrieval.
A list of collections with suitability notes and brief usage explanations for each.
Use get_document_summary to summarize a specific document, extracting its topic, key points, use cases, and whether it should be included in a RAG knowledge base.
A structured document summary that helps assess document value and ingestion priority.
Enable AI assistants to query knowledge bases and generate grounded answers.
Build and query vector knowledge bases for semantic search and RAG workflows.
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.
Use RAG tools for knowledge retrieval, document management, and search visualization.