head to head · open source
code-review-graph vs DeepAudit
code-review-graph has 31,548 GitHub stars, 2,870 forks, 163 open issues and last shipped yesterday. DeepAudit has 7,028 stars, 851 forks, 94 open issues and last shipped 2 days ago. code-review-graph leads on adoption by 349% (31,548 vs 7,028 stars). code-review-graph is written in Python under MIT; DeepAudit is written in Python under AGPL-3.0. code-review-graph has attracted 9% as many forks as stars, DeepAudit 12%. code-review-graph was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (code-review, llm), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| code-review-graph | DeepAudit | |
|---|---|---|
| GitHub stars | ★ 32K | ★ 7.0K |
| License | MIT | AGPL-3.0 |
| Written in | Python | Python |
| Last push | 2026-09-17 | 2026-09-16 |
| Forks | ⑂ 2.9K | ⑂ 851 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick code-review-graph if
- You weight community size — 32K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick DeepAudit if
- You want the DeepAudit feature set and don't need the biggest community
- You prefer the AGPL-3.0 license terms
- Your stack matches Python
- You evaluated both and DeepAudit fits your workflow better
About code-review-graph
code review graph is a local first code intelligence graph for MCP and the command line that parses a repository with Tree sitter into a persistent map of functions, classes, imports, calls, inheritance and test coverage, so AI coding assistants read only the files a review actually needs; it is aimed at developers and teams running AI coding tools against large repositories where repeated full codebase reads waste tokens.
read the full code-review-graph overview →
About DeepAudit
DeepAudit is an open source, AGPL 3.0 licensed multi agent system for mining code vulnerabilities, written in Python, that gives individual developers, small security teams, and DevSecOps groups an AI audit crew they can deploy and run themselves.
read the full DeepAudit overview →
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Frequently asked questions
Is code-review-graph or DeepAudit more popular?
code-review-graph has 31,548 GitHub stars and DeepAudit has 7,028. code-review-graph has the larger community by that measure.
Are code-review-graph and DeepAudit free?
Both are open source. code-review-graph is licensed under MIT and DeepAudit under AGPL-3.0. Neither carries a licence fee.
What is the difference between code-review-graph and DeepAudit?
code-review-graph is written in Python and DeepAudit in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, code-review-graph or DeepAudit?
Choose code-review-graph if you want the larger community (31,548 stars) or its MIT licence terms. Choose DeepAudit if its feature set, stack or AGPL-3.0 licence fits better. Both are self-hostable.