Type `/graphify` in your AI coding assistant and it maps your entire project — code, docs, PDFs, images, videos — into a knowledge graph you can query instead of grepping through files. Works in Claude Code, Codex, OpenCode, Cursor, Gemini CLI, GitHub Copilot CLI, VS Code Copilot Chat, Aider, OpenClaw, Factory Droid, Trae, Hermes, Kiro, Pi, and Google Antigravity. ``` /graphify . ``` That's it. You get three files: ``` graphify-out/ ├── graph.html open in any browser — click nodes, filter, search ├── GRAPH_REPORT.md the highlights: key concepts, surprising connections, suggested questions └── graph.json the full graph — query it anytime without re-reading your files ``` --- ## Install **Requires Python 3.10+** ```bash uv tool install graphifyy && graphify install # or: pipx install graphifyy && graphify install # or: pip install graphifyy && graphify install ``` > **Official package:** The PyPI package is `graphifyy` (double-y). Other `graphify*` packages on PyPI are not affiliated. The CLI command is still `graphify`. > **`graphify: command not found`?** Use `uv tool install graphifyy` or `pipx install graphifyy` — both put the CLI on PATH automatically. With plain `pip`, add `~/.local/bin` (Linux) or `~/Library/Python/3.x/bin` (Mac) to your PATH, or run `python -m graphify`. ### Pick your platform | Platform | Install command | |----------|----------------| | Claude Code (Linux/Mac) | `graphify install` | | Claude Code (Windows) | `graphify install --platform windows` | | Codex | `graphify install --platform codex` | | OpenCode | `graphify install --platform opencode` | | GitHub Copilot CLI | `graphify install --platform copilot` | | VS Code Copilot Chat | `graphify vscode install` | | Aider | `graphify install --platform aider` | | OpenClaw | `graphify install --platform claw` | | Factory Droid | `graphify install --platform droid` | | Trae | `graphify install --platform trae` | | Trae CN | `graphify install --platform trae-cn` | | Gemini CLI | `graphify install --platform gemini` | | Hermes | `graphify install --platform hermes` | | Kiro IDE/CLI | `graphify kiro install` | | Pi coding agent | `graphify install --platform pi` | | Cursor | `graphify cursor install` | | Google Antigravity | `graphify antigravity install` | > Codex users: also add `multi_agent = true` under `[features]` in `~/.codex/config.toml`. > Codex uses `$graphify` instead of `/graphify`. --- ## Make your assistant always use the graph Run this once in your project after building a graph: | Platform | Command | |----------|---------| | Claude Code | `graphify claude install` | | Codex | `graphify codex install` | | OpenCode | `graphify opencode install` | | GitHub Copilot CLI | `graphify copilot install` | | VS Code Copilot Chat | `graphify vscode install` | | Aider | `graphify aider install` | | OpenClaw | `graphify claw install` | | Factory Droid | `graphify droid install` | | Trae | `graphify trae install` | | Trae CN | `graphify trae-cn install` | | Cursor | `graphify cursor install` | | Gemini CLI | `graphify gemini install` | | Hermes | `graphify hermes install` | | Kiro IDE/CLI | `graphify kiro install` | | Pi coding agent | `graphify pi install` | | Google Antigravity | `graphify antigravity install` | This writes a small config file that tells your assistant to read `GRAPH_REPORT.md` before answering questions about your codebase. On platforms that support hooks (Claude Code, Codex, Gemini CLI), a hook fires automatically before every file-read call — your assistant navigates by the graph instead of grepping through everything. Uninstall with the matching command (e.g. `graphify claude uninstall`). --- ## What's in the report - **God nodes** — the most-connected concepts in your project. Everything flows through these. - **Surprising connections** — links between things that live in different files or modules. Ranked by how unexpected they are. - **The "why"** — inline comments (`# NOTE:`, `# WHY:`, `# HACK:`), docstrings, and design rationale from docs are extracted as separate nodes linked to the code they explain. - **Suggested questions** — 4–5 questions the graph is uniquely positioned to answer. - **Confidence tags** — every inferred relationship is marked `EXTRACTED`, `INFERRED`, or `AMBIGUOUS`. You always know what was found vs guessed. --- ## What files it handles | Type | Extensions | |------|-----------| | Code (25 languages) | `.py .ts .js .jsx .tsx .go .rs .java .c .cpp .rb .cs .kt .scala .php .swift .lua .zig .ps1 .ex .exs .m .jl .vue .svelte .sql` | | Docs | `.md .mdx .html .txt .rst .yaml .yml` | | Office | `.docx .xlsx` (requires `pip install graphifyy[office]`) | | PDFs | `.pdf` | | Images | `.png .jpg .webp .gif` | | Video / Audio | `.mp4 .mov .mp3 .wav` and more (requires `pip install graphifyy[video]`) | | YouTube / URLs | any video URL (requires `pip install graphifyy[video]`) | Code is extracted locally with no API calls (AST via tree-sitter). Everything else goes through your AI assistant's model API. --- ## Common commands ```bash /graphify . # build graph for current folder /graphify ./docs --update # re-extract only changed files /graphify . --cluster-only # rerun clustering without re-extracting /graphify . --no-viz # skip the HTML, just the report + JSON /graphify . --wiki # build a markdown wiki from the graph /graphify query "what connects auth to the database?" /graphify path "UserService" "DatabasePool" /graphify explain "RateLimiter" /graphify add https://arxiv.org/abs/1706.03762 # fetch a paper and add it /graphify add # transcribe and add a video graphify hook install # auto-rebuild on git commit graphify merge-graphs a.json b.json # combine two graphs ``` See the [full command reference](#full-command-reference) below. --- ## Ignoring files Create a `.graphifyignore` in your project root — same syntax as `.gitignore`, including `!` negation: ``` # .graphifyignore node_modules/ dist/ *.generated.py # only index src/, ignore everything else * !src/ !src/** ``` --- ## Team setup `graphify-out/` is meant to be committed to git so everyone on the team starts with a map. **Recommended `.gitignore` additions:** ``` graphify-out/manifest.json # mtime-based, breaks after git clone graphify-out/cost.json # local only # graphify-out/cache/ # optional: commit for speed, skip to keep repo small ``` **Workflow:** 1. One person runs `/graphify .` and commits `graphify-out/`. 2. Everyone pulls — their assistant reads the graph immediately. 3. Run `graphify hook install` to auto-rebuild after each commit (AST only, no API cost). 4. When docs or papers change, run `/graphify --update` to refresh those nodes. --- ## Using the graph directly ```bash # query the graph from the terminal graphify query "show the auth flow" graphify query "what connects DigestAuth to Response?" --graph graphify-out/graph.json # expose the graph as an MCP server (for repeated tool-call access) python -m graphify.serve graphify-out/graph.json ``` The MCP server gives your assistant structured access: `query_graph`, `get_node`, `get_neighbors`, `shortest_path`. > **WSL / Linux note:** Ubuntu ships `python3`, not `python`. Use a venv to avoid conflicts: > ```bash > python3 -m venv .venv && .venv/bin/pip install "graphifyy[mcp]" > ``` --- ## Privacy - **Code files** — processed locally via tree-sitter. Nothing leaves your machine. - **Video / audio** — transcribed locally with faster-whisper. Nothing leaves your machine. - **Docs, PDFs, images** — sent to your AI assistant's model API (Anthropic, OpenAI, etc.) using your own API key. - No telemetry, no usage tracking, no analytics. --- ## Full command reference ``` /graphify # run on current directory /graphify ./raw # run on a specific folder /graphify ./raw --mode deep # more aggressive relationship extraction /graphify ./raw --update # re-extract only changed files /graphify ./raw --directed # preserve edge direction /graphify ./raw --cluster-only # rerun clustering on existing graph /graphify ./raw --no-viz # skip HTML visualization /graphify ./raw --obsidian # generate Obsidian vault /graphify ./raw --wiki # build agent-crawlable markdown wiki /graphify ./raw --svg # export graph.svg /graphify ./raw --graphml # export for Gephi / yEd /graphify ./raw --neo4j # generate cypher.txt for Neo4j /graphify ./raw --neo4j-push bolt://localhost:7687 /graphify ./raw --watch # auto-sync as files change /graphify ./raw --mcp # start MCP stdio server /graphify add https://arxiv.org/abs/1706.03762 /graphify add /graphify add https://... --author "Name" --contributor "Name" /graphify query "what connects attention to the optimizer?" /graphify query "..." --dfs --budget 1500 /graphify path "DigestAuth" "Response" /graphify explain "SwinTransformer" graphify hook install # post-commit + post-checkout hooks graphify hook uninstall graphify hook status graphify claude install / uninstall graphify codex install / uninstall graphify opencode install graphify cursor install / uninstall graphify gemini install / uninstall graphify copilot install / uninstall graphify aider install / uninstall graphify claw install / uninstall graphify droid install / uninstall graphify trae install / uninstall graphify trae-cn install / uninstall graphify hermes install / uninstall graphify kiro install / uninstall graphify antigravity install / uninstall graphify clone https://github.com/karpathy/nanoGPT graphify merge-graphs a.json b.json --out merged.json graphify watch ./src graphify check-update ./src graphify update ./src graphify cluster-only ./my-project ``` --- ## Learn more - [How it works](docs/how-it-works.md) — the extraction pipeline, community detection, confidence scoring, benchmarks - [ARCHITECTURE.md](ARCHITECTURE.md) — module breakdown, how to add a language - [Optional integrations](docs/docker-mcp-sqlite.md) — Docker MCP Toolkit + SQLite --- ## Built on graphify — Penpax [**Penpax**](https://graphifylabs.ai) is the always-on layer built on top of graphify — it applies the same graph approach to your entire working life: meetings, browser history, emails, files, and code, updating continuously in the background. Built for people whose work lives across hundreds of conversations and documents they can never fully reconstruct. No cloud, fully on-device. **Free trial launching soon.** [Join the waitlist →](https://graphifylabs.ai) ---

Contributing

**Worked examples** are the most useful contribution. Run `/graphify` on a real corpus, save the output to `worked/{slug}/`, write an honest `review.md` covering what the graph got right and wrong, and open a PR. **Extraction bugs** — open an issue with the input file, the cache entry (`graphify-out/cache/`), and what was missed or wrong. See [ARCHITECTURE.md](ARCHITECTURE.md) for module responsibilities and how to add a language.