From Sushi to Semantics: A GraphRAG-Powered Japanese Food Explorer with Neo4j and MCP
summary
A Neo4j knowledge graph links dishes, ingredients, regions and historical notes and a working prototype answers cultural queries more accurately than ChatGPT alone, correcting errors like sashimi being labeled a sushi type and explaining why sushi appears at weddings; it combines Neo4j knowledge graph storage with GraphRAG + VectorRAG for semantic retrieval and LLM grounding and uses Model Context Protocol (MCP) for AI orchestration and multiagent coordination, and demo queries show clearer, provenance-backed answers.
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chapters (10)
- 0:00Introduction
- 0:55Why graphs for culture
- 3:07From knowledge to semantics
- 6:30Graph thinking and shared meaning
- 9:27Graph RAG and Neo4j
- 12:43Graph RAG vs vector RAG
- 13:46Model Context Protocol
- 14:07Demo results sushi explorer
- 17:10Lessons and future directions
- 18:17Summary and conclusion
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