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Intelligent RAG tool that chooses between private knowledge and web search.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Agentic RAG MCP Server" yet — see the docs or source repo.
Use Agentic RAG to decide whether to search the private knowledge base first, then answer: What are the rate limiting rules for our payment service API? If the knowledge base lacks the answer, supplement with web sources and cite them.
A knowledge-base-first answer, supplemented by web information if needed, with source citations.
Compare our internal RAG deployment approach with current public best practices. Automatically choose between the private knowledge base and web search, then output differences, risks, and improvement suggestions.
A comparative analysis combining internal and external sources, including recommendations and risks.
Answer this: Why did we adjust our recommendation system strategy last year? First decide whether to search internal meeting notes, product docs, or web sources, then provide a concise summary.
A concise explanation that prioritizes internal context and adds external context when necessary.
Build and query vector knowledge bases for semantic search and RAG workflows.
Turn unstructured documents into a searchable knowledge base for AI agents.
Search and add traceable RAG knowledge for each project workspace.
Expose modular retrieval and reasoning tools to AI assistants through MCP.
Centralize knowledge, run semantic search, ingest documents, and generate RAG answers.
Production-ready MCP server for query normalization, retrieval, and RAG prompt building.