GraphRAG

概要

This tool aims to significantly enhance information retrieval efficiency within enterprises by providing an Agent-facing Model Context Protocol (MCP) for document search. By leveraging the GraphRAG framework, it extracts user-relevant information from scattered documents, representing entities, relationships, and claims as a knowledge graph. This approach allows other agents to connect to a centralized document retrieval service, simplifying integration, improving scalability of intelligent agents, and delivering more structured, context-aware, and explainable responses than traditional RAG pipelines.

主な機能

• 1 GitHub stars
• Centralized document retrieval service for intelligent agents
• Semantic search and graph traversal for relevant information extraction
• Retrieval-Augmented Generation (RAG) using large language models
• Graph-based knowledge representation for enhanced context
• Caching mechanisms for improved efficiency in pipeline stages

ユースケース

• Extracting specific, user-relevant information from diverse enterprise documents for agent consumption
• Integrating and scaling intelligent agents across an enterprise by providing a unified document search API
• Generating accurate and context-rich answers grounded in a structured knowledge graph for complex queries