codegraph-mcpNo-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.
Why switchSame job — a code knowledge graph served to agents over MCP: codegraph-mcp bets on compliance (hash-chained audit of every read, cross-language HTTP edges); tokensave bets on breadth and token savings (50+ langs, 80+ tools, 12 agent integrations).
Full comparison → repowiseCodebase intelligence for AI and humans: deterministic code-health scores calibrated on real defects, graph-aware refactoring plans agents can execute, auto-docs and git analytics over 9 MCP tools.
Why switchBoth are code-intelligence MCP servers that cut agent context burn; tokensave answers structural questions (symbols, callers, impact) from a semantic graph, repowise layers health scoring and executable refactoring plans on top of its own graph.
Full comparison → cocoindexRust-core incremental indexing engine: declare Target = F(Source) in Python and it keeps vector/graph/relational targets fresh forever, reprocessing only the delta — with per-row lineage.
Why switchHead-to-head on the code-index-for-agents job: tokensave ships a pre-indexed libSQL+FTS5 semantic graph agents query over MCP; CocoIndex's flagship cocoindex-code does the same over MCP but incrementally re-indexed on every commit via the Δ engine.
Full comparison → Understand-AnythingPlugin 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.
Why switchSame 'index the codebase once, query the structure' idea: tokensave is a pre-indexed semantic graph agents hit instead of grepping (symbols, callers, impact radius); Understand Anything is the human-facing equivalent with tours, search and diff impact.
Full comparison →