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 → cocoindex-codeAST-based semantic code search for coding agents: pipx install, zero config, local embeddings out of the box — a CLI/skill/MCP that cuts agent context ~70% vs grepping. Built on CocoIndex.
Why switchSame job — replace agent grepping with a pre-built local index. TokenSave answers structural questions (symbols, callers, impact radius) from a semantic graph; cocoindex-code answers 'where is the code that does X' via AST-chunked embedding search.
Full comparison → codebase-memory-mcpCode intelligence MCP in pure C: tree-sitter knowledge graph over 158 languages, average repo indexed in milliseconds, sub-ms queries, 10x fewer tokens. Single static binary, zero deps.
Why switchThe same exact job — pre-indexed structural code intelligence over MCP so agents stop grepping. TokenSave is a libSQL semantic graph across 50+ languages; codebase-memory is a zero-dependency C binary betting everything on speed: 158 languages, sub-ms.
Full comparison → gortexCode-intelligence engine in one static Go binary: tree-sitter graph over 257 languages, compiler-grade resolution for 17, multi-repo, 175 configurable MCP tools — up to 50x fewer tokens. 100% local.
Why switchSame pitch — a pre-indexed semantic graph agents query instead of grepping. tokensave is the lean libSQL take; gortex scales the same idea to multi-repo and 257 languages.
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 → serenaThe IDE for your coding agent: an MCP toolkit giving symbol-level retrieval, editing, refactoring and debugging over real language servers — or a JetBrains plugin backend.
Why switchBoth replace grepping with a queryable code model. tokensave pre-indexes a semantic graph in libSQL and answers symbols, callers and impact radius in one call; Serena offers IDE-grade editing and refactoring on top of retrieval, not just lookup.
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 → GraftContext layer for large codebases: a graph of plain-English markdown nodes — no embeddings, no index — agents read like any repo file. Claude Code hooks + MCP; 42% fewer tokens in its bench.
Why switchBoth replace blind grepping with a pre-built codebase understanding: tokensave is a queryable semantic index (libSQL + FTS5) behind MCP tools; Graft is prose-first — explanation files injected via hooks, no query API to learn.
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 →