Local-first MCP graph intelligence server providing RRF hybrid search, multi-hop traversal, source snippets, and rationale nodes for AI agents, without Docker or web UI.
A local-first, LLM-agnostic MCP server that lets you ask hard questions about your documents, media, and code, and get traceable answers entirely offline.
A local-first MCP server that transforms crypto whitepapers into a knowledge graph and vector corpus, enabling entity-filtered RAG question answering with optional knowledge graph enrichment.
An open-source MCP server for RAG over personal documents. Supports three parallel strategies — Traditional, Contextual, and Graph RAG — with all data stored locally for privacy.
MCP server for building knowledge graphs from documents. It ingests PDF/PPTX/DOCX files, transcribes to Markdown, and uses LLM to bootstrap entity patterns and build a JSONL knowledge graph with RAG chunks.