Enables AI assistants to manage documents, query knowledge graphs, and perform retrieval-augmented generation using LightRAG with 30 tools and multiple query modes.
Enables advanced RAG with knowledge graphs, supporting document ingestion, multimodal extraction, and multiple query modes (naive, local, global, hybrid) via the Model Context Protocol.
Enables AI assistants to interact with LightRAG knowledge graphs, supporting smart upsert for Obsidian vaults, semantic queries, and document/graph management.
Provides a comprehensive Model Context Protocol interface for RAGFlow, enabling AI models to perform semantic retrieval, manage datasets, and handle document chunks. It supports advanced features like GraphRAG and RAPTOR for sophisticated knowledge base management and natural language querying.
Provides AI assistants with persistent graph database memory using Neo4j, enabling task management, relationship understanding, semantic search with embeddings, file indexing, and multi-agent coordination through the Model Context Protocol.
An MCP server for document parsing, ingestion, query (including multimodal), and lightweight knowledge graph inspection, enabling RAG workflows via the Model Context Protocol.