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Use authenticated MCP tools for graph-augmented and hybrid RAG retrieval.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "rag-mcp" yet — see the docs or source repo.
Use rag-mcp to call the authenticated retrieval endpoints for 'MCP best practices in the enterprise knowledge base'. Run both graph-augmented retrieval and hybrid retrieval, then return the top 5 results for each method with sources and a brief comparison.
A list of results from both retrieval modes, source information, and a short comparison of recall and relevance.
Use rag-mcp to demonstrate a JWT-authenticated retrieval call for '2024 product roadmap'. Indicate whether authentication succeeded, which retrieval mode was used, and which key documents were returned.
An authentication success or failure result, plus the retrieval mode, matched documents, and a summary of key content.
Using rag-mcp, run both graph-augmented retrieval and hybrid retrieval for the question 'What cross-department dependencies exist in the customer complaint handling process?' Compare the completeness, relationships, and best-fit scenarios of the results.
A side-by-side comparison of both retrieval methods to show which is better for relationship-heavy or standard semantic queries.
Retrieve relevant context and metadata from Qdrant using natural language queries.
Turn unstructured documents into a searchable knowledge base for AI agents.
Expose modular retrieval and reasoning tools to AI assistants through MCP.
Index documents and retrieve relevant context for better LLM responses.
Let AI securely query private local documents with persistent memory.
Build production-grade RAG systems with hybrid retrieval and agentic reasoning.