What problem does it solve? Understanding a new codebase, research corpus, or mixed folder of notes requires reading everything manually, and connections across documents stay invisible. Graphify turns any folder into a persistent, queryable knowledge graph with community detection and an honest audit trail showing which relationships were extracted versus inferred. ## Core Features & Use Cases - Hybrid extraction pipeline: Combines deterministic AST parsing for code with parallel LLM subagents for docs, papers, and images, with caching for incremental updates. - Community detection and analysis: Clusters the graph, labels communities, finds god nodes and surprising cross-document connections, and generates a plain-language GRAPH_REPORT.md. - Multiple export targets: Produces interactive HTML, GraphRAG-ready JSON, Obsidian vaults, SVG, GraphML, Neo4j Cypher/push, and an MCP server for live agent queries. - Use Case: Point it at an unfamiliar repository to get a navigable architecture graph before touching any code, or drop papers, tweets, and notes into a folder and query the combined concept graph weeks later without re-reading. ## Quick Start Run /graphify on the current directory to build a knowledge graph and open the generated graph.html report.
