GitHub - dumbledore2002/MeowGraph: Visualize any Graphify knowledge graph interactively. Drop a graph.json explore code, schemas, docs, and infrastructure as a force-directed network. Search nodes, find paths, export. Runs in browser.

OFFICIAL CA :

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, Kimi Code, 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

For a readable architecture page with Mermaid call-flow diagrams, run:

graphify export callflow-html

Prerequisites

Requirement	Minimum	Check	Install
Python	3.10+	`python --version`	python.org
uv (recommended)	any	`uv --version`	`curl -LsSf https://astral.sh/uv/install.sh \| sh`
pipx (alternative)	any	`pipx --version`	`pip install pipx`

macOS quick install (Homebrew):

brew install python@3.12 uv

Windows quick install:

winget install astral-sh.uv

Ubuntu/Debian:

sudo apt install python3.12 python3-pip pipx
# or install uv:
curl -LsSf https://astral.sh/uv/install.sh | sh

Install

Official package: The PyPI package is graphifyy (double-y). Other graphify* packages on PyPI are not affiliated. The CLI command is still graphify.

Step 1 — install the package:

# Recommended (uv puts graphify on PATH automatically):
uv tool install graphifyy

# Alternatives:
pipx install graphifyy
pip install graphifyy

Step 2 — register the skill with your AI assistant:

graphify install

That's it. Open your AI assistant and type /graphify .

PowerShell note: Use graphify . not /graphify . — the leading slash is a path separator in PowerShell.

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`
Kimi Code	`graphify install --platform kimi`
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.

Optional extras

Install only what you need:

Extra	What it adds	Install
`pdf`	PDF extraction	`pip install "graphifyy[pdf]"`
`office`	`.docx` and `.xlsx` support	`pip install "graphifyy[office]"`
`google`	Google Sheets rendering	`pip install "graphifyy[google]"`
`video`	Video/audio transcription (faster-whisper + yt-dlp)	`pip install "graphifyy[video]"`
`mcp`	MCP stdio server	`pip install "graphifyy[mcp]"`
`neo4j`	Neo4j push support	`pip install "graphifyy[neo4j]"`
`svg`	SVG graph export	`pip install "graphifyy[svg]"`
`leiden`	Leiden community detection (Python < 3.13 only)	`pip install "graphifyy[leiden]"`
`ollama`	Ollama local inference	`pip install "graphifyy[ollama]"`
`openai`	OpenAI / OpenAI-compatible APIs	`pip install "graphifyy[openai]"`
`gemini`	Google Gemini API	`pip install "graphifyy[gemini]"`
`bedrock`	AWS Bedrock (uses IAM, no API key)	`pip install "graphifyy[bedrock]"`
`sql`	SQL schema extraction	`pip install "graphifyy[sql]"`
`all`	Everything above	`pip install "graphifyy[all]"`

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`
Kimi Code	`graphify install --platform kimi`
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.

To remove graphify from all platforms at once: graphify uninstall (add --purge to also delete graphify-out/). Or use the per-platform 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 (29 languages)	`.py .ts .js .jsx .tsx .mjs .go .rs .java .c .cpp .h .hpp .rb .cs .kt .scala .php .swift .lua .luau .zig .ps1 .ex .exs .m .mm .jl .vue .svelte .astro .groovy .gradle .dart .v .sv .sql .f .f90 .f95 .f03 .f08 .pas .pp .dpr .dpk .lpr .inc .dfm .lfm .lpk`
Docs	`.md .mdx .qmd .html .txt .rst .yaml .yml`
Office	`.docx .xlsx` (requires `pip install graphifyy[office]`)
Google Workspace	`.gdoc .gsheet .gslides` (opt-in; requires `gws` auth and `--google-workspace`; Sheets need `pip install graphifyy[google]`)
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.

Google Drive for desktop .gdoc, .gsheet, and .gslides files are shortcut pointers, not document content. To include native Google Docs, Sheets, and Slides in a headless extraction, install and authenticate the gws CLI, then run:

pip install "graphifyy[google]"  # needed for Google Sheets table rendering
gws auth login -s drive
graphify extract ./docs --google-workspace

You can also set GRAPHIFY_GOOGLE_WORKSPACE=1. Graphify exports shortcuts into graphify-out/converted/ as Markdown sidecars, then extracts those files.

Common commands

/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 export callflow-html      # architecture/call-flow HTML from graphify-out/

/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 <youtube-url>                       # 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 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:

One person runs /graphify . and commits graphify-out/.
Everyone pulls — their assistant reads the graph immediately.
Run graphify hook install to auto-rebuild after each commit (AST only, no API cost). This also sets up a git merge driver so graph.json is never left with conflict markers — two devs committing in parallel get their graphs union-merged automatically.
When docs or papers change, run /graphify --update to refresh those nodes.

Using the graph directly

# 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

# register with Kimi Code:
kimi mcp add --transport stdio graphify -- 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:
python3 -m venv .venv && .venv/bin/pip install "graphifyy[mcp]"

Environment variables

These are only needed for headless / CI extraction (graphify extract). When running via the /graphify skill inside your IDE, the model API is provided by your IDE session — no extra keys needed.

Variable	Used for	When required
`ANTHROPIC_API_KEY`	Claude (Anthropic) backend	`--backend claude`
`GEMINI_API_KEY` or `GOOGLE_API_KEY`	Google Gemini backend	`--backend gemini`
`OPENAI_API_KEY`	OpenAI or OpenAI-compatible APIs	`--backend openai`
`MOONSHOT_API_KEY`	Kimi Code backend	`--backend kimi`
`OLLAMA_BASE_URL`	Ollama local inference URL	`--backend ollama` (default: `http://localhost:11434`)
`OLLAMA_MODEL`	Ollama model name	`--backend ollama` (default: auto-detect)
`GRAPHIFY_OLLAMA_NUM_CTX`	Override Ollama KV-cache window size	optional — auto-sized by default
`GRAPHIFY_OLLAMA_KEEP_ALIVE`	Minutes to keep Ollama model loaded	optional — set `0` to unload after each chunk
`AWS_*` / `~/.aws/credentials`	AWS Bedrock — standard credential chain	`--backend bedrock` (no API key, uses IAM)
`GRAPHIFY_MAX_WORKERS`	AST parallelism thread count	optional — also `--max-workers` flag
`GRAPHIFY_MAX_OUTPUT_TOKENS`	Raise output cap for dense corpora	optional — e.g. `32768` for large files
`GRAPHIFY_API_TIMEOUT`	HTTP timeout in seconds (default: 600)	optional — also `--api-timeout` flag
`GRAPHIFY_FORCE`	Force graph rebuild even with fewer nodes	optional — also `--force` flag
`GRAPHIFY_GOOGLE_WORKSPACE`	Auto-enable Google Workspace export	optional — set to `1`

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 for semantic extraction (via the /graphify skill, using whatever model your IDE session runs). Headless graphify extract requires GEMINI_API_KEY / GOOGLE_API_KEY (Gemini), MOONSHOT_API_KEY (Kimi), ANTHROPIC_API_KEY (Claude), OPENAI_API_KEY (OpenAI), a running Ollama instance (OLLAMA_BASE_URL), AWS credentials via the standard provider chain (Bedrock - no API key needed, uses IAM), or the claude CLI binary (Claude Code - no API key needed, uses your Claude subscription). The --dedup-llm flag uses the same key.
No telemetry, no usage tracking, no analytics.

Troubleshooting

graphify: command not found after pip install graphifyy pip installs scripts to a user bin directory that may not be on your PATH. Fix:

macOS: add ~/Library/Python/3.x/bin to your PATH in ~/.zshrc
Linux: add ~/.local/bin to your PATH in ~/.bashrc
Or use uv tool install graphifyy / pipx install graphifyy — both manage PATH automatically.

python -m graphify works but graphify command doesn't Your shell's PATH doesn't include the Python scripts directory. Use uv or pipx instead of plain pip.

/graphify . causes "path not recognized" in PowerShell PowerShell treats a leading / as a path separator. Use graphify . (no slash) on Windows.

Graph has fewer nodes after --update or rebuild If a refactor deleted files, the old nodes linger. Pass --force (or set GRAPHIFY_FORCE=1) to overwrite even when the rebuild has fewer nodes.

Graph has duplicate nodes for the same entity (ghost duplicates) This happens when semantic and AST extraction disagreed on the node ID format. Run a full re-extract to clean up:

graphify extract . --force

Ollama runs out of VRAM / context window exceeded The KV-cache window is auto-sized but may be too large for your GPU. Reduce it:

GRAPHIFY_OLLAMA_NUM_CTX=8192 graphify extract ./docs --backend ollama --token-budget 4000

Graph HTML is too large to open in a browser (>5000 nodes) Skip HTML generation and use the JSON directly:

graphify cluster-only ./my-project --no-viz
graphify query "..."

graph.json has conflict markers after two devs commit at once Run graphify hook install — it sets up a git merge driver that union-merges graph.json automatically so conflicts never happen.

Extraction returns empty nodes/edges for docs or PDFs Docs and PDFs require an LLM call. Check that your API key is set and the backend is correct:

ANTHROPIC_API_KEY=sk-... graphify extract ./docs --backend claude

Skill version mismatch warning in your IDE Your installed graphify version is different from the skill file. Update:

uv tool upgrade graphifyy
graphify install  # overwrites the skill file

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 <video-url>
/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 uninstall                 # remove from all platforms in one shot
graphify uninstall --purge         # also delete graphify-out/

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 extract ./docs                        # headless LLM extraction for CI (no IDE needed)
graphify extract ./docs --backend gemini       # explicit backend: gemini, kimi, claude, openai, ollama, bedrock, or claude-cli
graphify extract ./docs --backend gemini --model gemini-3.1-pro-preview
graphify extract ./docs --backend ollama       # local Ollama (set OLLAMA_BASE_URL / OLLAMA_MODEL) - no API key needed for loopback
GRAPHIFY_OLLAMA_NUM_CTX=32768 graphify extract ./docs --backend ollama   # override KV-cache window (auto-sized by default)
GRAPHIFY_OLLAMA_KEEP_ALIVE=0 graphify extract ./docs --backend ollama    # unload model after each chunk (saves VRAM on small GPUs)
graphify extract ./docs --backend bedrock      # AWS Bedrock via IAM - no API key, uses AWS credential chain
graphify extract ./docs --backend claude-cli   # route through Claude Code CLI - no API key, uses your Claude subscription
graphify extract ./docs --max-workers 16       # AST parallelism (also GRAPHIFY_MAX_WORKERS)
graphify extract ./docs --token-budget 30000   # smaller semantic chunks for local/small models
graphify extract ./docs --max-concurrency 2    # fewer parallel LLM calls (useful for local inference)
graphify extract ./docs --api-timeout 900      # longer HTTP timeout for slow local models (default 600s)
graphify extract ./docs --google-workspace     # export .gdoc/.gsheet/.gslides via gws before extraction
graphify extract ./docs --no-cluster           # raw extraction only, skip clustering
graphify extract ./docs --force                # overwrite graph.json even if new graph has fewer nodes (use after refactors or to clear ghost duplicates)
graphify extract ./docs --dedup-llm            # LLM tiebreaker for ambiguous entity pairs (uses same API key)
graphify extract ./docs --global --as myrepo   # extract and register into the cross-project global graph
GRAPHIFY_MAX_OUTPUT_TOKENS=32768 graphify extract ./docs --backend claude  # raise output cap for dense corpora

graphify export callflow-html                       # graphify-out/<project>-callflow.html
graphify export callflow-html --max-sections 8      # cap generated architecture sections
graphify export callflow-html --output docs/arch.html
graphify export callflow-html ./some-repo/graphify-out

graphify global add graphify-out/graph.json myrepo   # register a project graph into ~/.graphify/global.json
graphify global remove myrepo                         # remove a project from the global graph
graphify global list                                  # show all registered repos + node/edge counts
graphify global path                                  # print path to the global graph file

graphify clone https://github.com/karpathy/nanoGPT
graphify merge-graphs a.json b.json --out merged.json
graphify --version                                    # print installed version
graphify watch ./src
graphify check-update ./src
graphify update ./src
graphify update ./src --no-cluster  # skip reclustering, write raw AST graph only
graphify update ./src --force       # overwrite even if new graph has fewer nodes
graphify cluster-only ./my-project
graphify cluster-only ./my-project --graph path/to/graph.json  # custom graph location

Learn more

How it works — the extraction pipeline, community detection, confidence scoring, benchmarks
ARCHITECTURE.md — module breakdown, how to add a language
Optional integrations — Docker MCP Toolkit + SQLite

Built on graphify — Penpax

Penpax 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 →

Contributing

Development setup

Clone the repo and install in editable mode:

git clone https://github.com/safishamsi/graphify.git
cd graphify
git checkout v7                        # active development branch

# Create a virtual environment (Python 3.10+ required):
python3 -m venv .venv
source .venv/bin/activate              # Windows: .venv\Scripts\activate

# Install in editable mode with all optional extras:
pip install -e ".[all]"

Verify the editable install:

graphify --version
python -c "import graphify; print(graphify.__file__)"

Running tests

pip install pytest
pytest tests/ -q                       # run the full suite
pytest tests/test_extract.py -q        # one module
pytest tests/ -q -k "python"           # filter by name

macOS note: the test suite includes both sample.f90 and sample.F90 fixtures. These collide on case-insensitive HFS+ / APFS file systems. Run on Linux or in a Docker container if you need to test both Fortran variants simultaneously.

Git workflow

Active development happens on the v7 branch.
Commit style: fix: <description> / feat: <description> / docs: <description>
Before opening a PR, run pytest tests/ -q and confirm it passes.
Add a fixture file to tests/fixtures/ and tests to tests/test_languages.py for any new language extractor.

What to contribute

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 for module responsibilities and how to add a language.

Name		Name	Last commit message	Last commit date
Latest commit History 444 Commits
.github		.github
docs		docs
graphify		graphify
tests		tests
worked		worked
.gitignore		.gitignore
AGENTS.md		AGENTS.md
ARCHITECTURE.md		ARCHITECTURE.md
CHANGELOG.md		CHANGELOG.md
LICENSE		LICENSE
README.md		README.md
SECURITY.md		SECURITY.md
index.html		index.html
pyproject.toml		pyproject.toml

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Prerequisites

Install

Pick your platform

Optional extras

Make your assistant always use the graph

What's in the report

What files it handles

Common commands

Ignoring files

Team setup

Using the graph directly

Environment variables

Privacy

Troubleshooting

Full command reference

Learn more

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Team setup

Using the graph directly

Environment variables

Privacy

Troubleshooting

Full command reference

Learn more

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