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codegraph-mcp vs Understand-Anything

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 — Plugin for Claude Code and 16 other hosts that turns any codebase into an interactive knowledge graph — multi-agent analysis, layered dashboard, guided tours, diff-impact view, domain mapping.

The curated verdict

Both build knowledge graphs of your codebase, for opposite consumers: codegraph-mcp serves symbols, call edges and blast-radius queries to AI agents over MCP with an audit chain; Understand Anything renders an interactive dashboard for human comprehension and onboarding.

codegraph-mcpUnderstand-Anything
Stars575k
Forks06.2k
LanguagePythonTypeScript
LicenseNOASSERTIONMIT
Last activity12 days agoyesterday
Topicscoding, ragcoding
Curated connections43

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.

Understand-Anything — the curator's take

The onboarding killer app, and its motto is the right one: graphs that teach, not graphs that impress. /understand runs a multi-agent pipeline over the repo, then the dashboard gives you architecture layers, dependency-ordered guided tours, semantic search, diff blast-radius, and a business-domain view that maps code to real processes. The team trick is the sleeper: the graph is plain JSON — commit it once and every teammate skips the analysis. Incremental re-runs + a post-commit auto-update hook keep it fresh. Budget real tokens for the first full run on a large repo (their own warning), or point it at a local model. NOT an agent context server — this graph is for humans first; when you want a code graph served TO agents over MCP, that's codegraph-mcp or tokensave territory.