MiniRAG
Provides efficient retrieval-augmented generation through naive vector database querying and smart graph-based retrieval using entity relationships, returning answers with cited sources in JSON format for knowledge retrieval workflows requiring both speed and accuracy in document-based question answ
About
An MCP server wrapper around MiniRAG that provides efficient retrieval-augmented generation capabilities through two distinct approaches: naive vector database querying and smart graph-based retrieval using entity relationships and reasoning paths. Leverages client-managed LLM inference with structured output constraints for enhanced reliability, while simplifying MiniRAG setup through UV dependency management. Supports configurable embedding providers including Ollama and OpenAI-compatible services, returning answers with cited sources in JSON format for knowledge retrieval workflows optimized for small language models.
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