# Graphify turns codebases into queryable knowledge graphs for AI assistants

> **Key takeaway:** Graphify is an open-source tool that uses tree-sitter AST parsing to build local, deterministic knowledge graphs from codebases, letting developers query project structure through AI assistants without vector stores or sending code to remote LLMs.

**Published:** 2026-10-21T12:05:03.278441+00:00 
**Source:** GitHub Trending (daily) 
**Category:** foss-apps 
**Canonical URL:** https://fosswire.org/news/graphify-turns-codebases-into-queryable-knowledge-graphs-for.html 

## Summary
Graphify-Labs released Graphify, a CLI tool that integrates with Claude Code, Cursor, Codex, Gemini CLI and 20+ other AI coding assistants. It parses code locally using tree-sitter to generate deterministic knowledge graphs with labeled edges (EXTRACTED or INFERRED), producing queryable graph.json, browsable graph.html, and a GRAPH_REPORT.md. The tool requires Python 3.10+ and supports ~40 languages for cross-file resolution. A proprietary Graphify Cloud service offers continuous graph updates, monorepo support, and third-party connectors.

## How Graphify builds and queries code graphs
- **Local-first parsing**: Code analysis uses tree-sitter AST with no LLM involvement; only docs, PDFs, images and video use a configured model for semantic processing
- **Deterministic output**: Every edge is tagged either EXTRACTED (explicit in source) or INFERRED (derived by resolution), with no embeddings or vector store
- **Three output files**: graph.html (interactive browser visualization), GRAPH_REPORT.md (key concepts and suggested questions), graph.json (full queryable graph with schema_version and graphify_version fields)
- **Cross-language support**: Resolves calls, imports, inherits, and mixes_in across approximately 40 languages via tree-sitter
- **Graph algorithms**: Uses Leiden community detection for subsystem identification and calculates "god nodes" for most-connected concepts
- **CLI commands**: `graphify explain <node>`, `graphify path <A> <B>`, `graphify query "<question>"` for scoped subgraph retrieval

## Why it matters
The tool addresses growing developer concern about token costs and data privacy when using AI assistants with large codebases, offering a verifiable alternative to opaque RAG systems. Its open-source core and broad assistant support could reduce lock-in to any single AI coding platform.