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Retrieve relevant document chunks and generate suggested LLM prompts via REST and MCP.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-rag-mini" yet — see the docs or source repo.
Query the knowledge base for document chunks most relevant to “vector database index update strategies” and return the suggested final prompt for an LLM.
Returns several top relevant document chunks and a ready-to-use reference prompt for an LLM.
Retrieve existing documentation related to “REST API authentication methods,” assemble the most relevant context, and provide an LLM prompt suitable for summarization.
Outputs context chunks related to authentication methods, plus a suggested prompt for generating a summary.
Search the internal knowledge index for content related to “employee reimbursement process,” return the best-matching chunks, and generate a prompt template for answering employee questions.
Provides reimbursement-related chunks and a Q&A prompt template suitable for a support or knowledge assistant.
Index documents and retrieve relevant context for better LLM responses.
Turn unstructured documents into a searchable knowledge base for AI agents.
Retrieve relevant context and metadata from Qdrant using natural language queries.
Connect AI agents to secure RAG workflows across multiple vector databases.
Let AI securely query private local documents with persistent memory.
Search local Markdown files and return full document contents for use.