graphify vs Graft
graphify is much bigger: 114.9k stars against 5.6k. Over the days we have tracked them graphify moved +27.4% and Graft +1199.3%, so Graft is growing faster right now.
Neither one leads on the six capability axes, so the choice comes down to which of them fits the way you already work.
Stars and commit dates come from our own daily tracking. The six axes are read off each project's documentation by our review pipeline, so they describe what a project says about itself, not what we measured in its code.
Where they stand today
Builds a deterministic, AST-based, repo-wide knowledge graph (no embeddings or vector store) with every edge labeled EXTRACTED or INFERRED.
- Stars
- 114.9k
- Tracked growth
- +27.4%
- Maturity
- ●●●●●
- Last commit
- 10h ago
- Language
- Python
- License
- Apache-2.0
- Cost to run
- Free for code (local); optional API key for semantic media/docs
Persists a deterministic, human-readable context graph as markdown files inside the repo (no embeddings or external index), so agents can follow real files and share an up-to-date code understanding via git.
- Stars
- 5.6k
- Tracked growth
- +1199.3%
- Maturity
- ●●●●●
- Last commit
- 1d ago
- Language
- TypeScript
- License
- MIT
- Cost to run
- Your API key; provider billing applies.
Six axes, head to head
Each axis runs 0 to 5. The label under a score is what that project's own docs claim, not a category average.
| Axis | graphify | Graft |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Whole-repo analysis | ●●●●● Whole-repo graph |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● Edge confidence tags | ●●●●● Ranking & checks |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Configurable install & extras | ●●●●● Config & flags |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Fully local possible | ●●●●● Self-hostable |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● Bring-your-own model | ●●●●● Bring-your-key |
Setup ease What it takes to get a first useful run out of it. | ●●●●● Quick CLI install | ●●●●● One-command init |
Which one to pick
Pick graphify if…
Local-first — map your entire codebase into a queryable knowledge graph with deterministic tree-sitter parsing, minimal LLM use, and explainable edges.
Pick Graft if…
Easy setup — one-command init builds a local, versionable code-graph and wires directly into coding agents (Claude Code et al.) to cut tokens, tool calls, and latency.
What people want from each one
Graphify-Labs/graphify
NanoNets/Graft
Questions people ask
Is graphify better than Graft?
Neither one leads on the six capability axes, so the choice comes down to which of them fits the way you already work. graphify is worth picking when local-first — map your entire codebase into a queryable knowledge graph with deterministic tree-sitter parsing, minimal LLM use, and explainable edges.
Which of graphify and Graft keeps my code private?
graphify: Fully local possible (5/5). Graft: Self-hostable (4/5).
What does each one cost to run?
graphify: Free for code (local); optional API key for semantic media/docs. Graft: Your API key; provider billing applies..
Full profiles: Graphify-Labs/graphify and NanoNets/Graft. Everything else in Codebase context.