code-review-graph vs ripwire
Local-first code intelligence graph for AI coding tools: Tree-sitter AST graph + blast-radius analysis served over MCP, so agents read ~82x fewer tokens per review question. — versus — Red Hat's 'ripgrep of AI context': a zero-dependency C++23 CLI + MCP that hands a coding agent a ranked call graph — what to touch, blast radius, tests to run — with no index server.
Both compute a Tree-sitter-style call graph and blast-radius for agents; code-review-graph is a Python MCP with a persisted graph, ripwire is a single offline C++ binary that rebuilds in ~0.3s and adds tests-to-run and quality deltas.
| code-review-graph | ripwire | |
|---|---|---|
| Stars | 31k | 1.9k |
| Forks | 2.8k | 111 |
| Language | Python | C++ |
| License | MIT | Apache-2.0 |
| Last activity | yesterday | yesterday |
| Topics | code-intel | code-intel, coding |
| Curated connections | 6 | 7 |
code-review-graph — the curator's take
The rare benchmark-honest repo: it tells you the 528x number is the best case and its recall metric is circular. Install once, it configures 14 platforms (Codex, Claude Code, Cursor...). Reach for it on monorepos where review context is the token sink; skip on small repos where a grep costs less than the graph's own metadata.
ripwire — the curator's take
Reach for this when you want code-context for an agent with the operational profile of ripgrep: one static binary, indexes a repo in well under a second on a few MB, no daemon, no embeddings, no API key — and it ships skills that tell Claude Code/Codex/Cursor/aider *when* to call it. The `--for="<change>"` mode (rank by intended change, then blast radius + tests-to-run + McCabe/Halstead quality deltas) is the differentiator over plain symbol graphs. Prefer the CLI; the MCP schema costs context every session. Not for you if you need a persistent, queryable graph across repos, natural-language-to-Cypher, or semantic search — it is deterministic and lexical/structural only.