Graphify-Labsgraphify
Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing, every edge explained, no vector store.
TL;DR · 30-second scan
graphify (Python) — Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing, every edge explained, no vector store.
You want an AI tool to answer structural questions about a large codebase with traceable, non-hallucinated references.
Search · AI & ML
Turns a codebase — with its docs, SQL schemas, configs and PDFs — into a queryable knowledge graph, using deterministic AST parsing through tree-sitter rather than embeddings. That design choice is the whole argument: there is no vector store, no similarity guessing, and every edge in the graph can be explained by the code that produced it. For questions like "what actually calls this function" it beats semantic search, which returns things that merely look related. Python, Apache-2.0, and it installs as a skill for Claude Code, Cursor, Codex and Gemini CLI. Tradeoffs: AST parsing binds it to supported languages, graph construction on a large repository is slow and memory-hungry, and 1,182 open issues reflects how young and fast-moving it is.
You want an AI tool to answer structural questions about a large codebase with traceable, non-hallucinated references.
Your stack is in a language its parsers do not cover, or your repository is too large to graph comfortably.
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