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codegraph-mcp vs ripwire

No-train, on-prem code knowledge graph served to AI agents over MCP — symbols, call edges, cross-language links and blast-radius queries, with a hash-chained audit log of every read. — 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.

The curated verdict

Both serve a no-train, on-prem code knowledge graph to agents; ripwire is the no-server variant and explicitly benchmarks itself against graph-database code-context MCP servers on index time and memory.

codegraph-mcpripwire
Stars71.9k
Forks0111
LanguagePythonC++
LicenseNOASSERTIONApache-2.0
Last activity2 months agoyesterday
Topicscode-intel, ragcode-intel, coding
Curated connections127

codegraph-mcp — the curator's take

Niche but real: if agents must understand code that cannot leave your building AND compliance asks 'what exactly did the agent read', the tamper-evident audit chain is the only game in town; cross-language call edges (TS fetch → Go/Python handler) catch what one-file context misses. NOT for most teams yet: 5 stars, single vendor, and — deal-breaker until fixed — no clear open-source license (NOASSERTION on GitHub). Treat it as an evaluation candidate, not a dependency.

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.