GitHub Trending · Agent Tooling · Updated
Graphify-Labs/graphify
An AI skill that turns a whole project folder into a queryable knowledge graph
- Stars at last chart appearance
- ★ 114.4k
- Language
- Python
- Chart appearances
- 0
- On-chart tracking
- 0 days tracked
What it does
A skill for Claude Code, Codex, OpenCode, Cursor, Gemini CLI and more: type /graphify and your entire project — code, SQL schemas, docs, PDFs, images, videos — is mapped into a queryable knowledge graph, replacing grep-and-scroll. Code parsing uses tree-sitter AST: deterministic, no LLM, fully local; only document content goes through a model. Not a vector index — a real graph, with every edge labeled EXTRACTED (read directly) or INFERRED.
What's inside
Distributed as a CLI (PyPI package graphifyy, install via uv tool install or pipx); the repo holds docs/ (README translations in 30+ languages) and interactive graph.html visualizations; default branch v8, iterating fast.
Tech stack
Python + tree-sitter, outputting force-directed HTML graphs; hooks into each CLI assistant as a skill.
Use cases
- Developers inheriting large legacy projects — one command maps the codebase into a knowledge graph
- Heavy AI users — swap vector RAG for graph context that retrieves the right thing
- Docs teams — fold docs, PDFs and diagrams into one queryable graph
Why it's trending
Its knowledge-graph alternative to vector-only retrieval speaks directly to limitations teams encounter when building contextual AI assistants.
Current chart placements
| Period | Language filter | Rank | Stars gained |
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Editorial summaries are based on the public repository and the dated GitHub Trending snapshot. Verify implementation details in the upstream repository.