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Connect AI to LightRAG for semantic search, ingestion, and graph management.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-lightrag" yet — see the docs or source repo.
Use mcp-lightrag to smart-upsert my Obsidian vault, deduplicate content, build the knowledge graph, and return a summary of the import results.
A summary of imported documents, deduplication results, graph construction status, and any issues found.
Use mcp-lightrag to query the most common performance issues in product feedback from the past three months and their related modules, then organize the answer by importance.
An organized answer based on the knowledge graph and semantic retrieval, with supporting documents or nodes.
Use mcp-lightrag to inspect the current knowledge graph for isolated nodes, duplicate documents, and broken references, then provide cleanup recommendations.
A graph health report highlighting problematic items and actionable cleanup recommendations.
Connect AI assistants to LightRAG for document management and multi-mode knowledge queries.
Connect LightRAG through MCP for unified retrieval and knowledge QA integration.
Ask graph-aware questions and search Obsidian vaults with local-first AI retrieval.
Search and add traceable RAG knowledge for each project workspace.
Enable AI to semantically search and retrieve relevant Obsidian notes.
Connect AI to an Obsidian vault for semantic search and graph-based knowledge operations.