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cocoindex-code vs tokensave

AST-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. — versus — Code-intelligence MCP server for coding agents — a pre-indexed semantic graph (libSQL + FTS5) they query instead of grepping: symbols, callers, impact radius in one call. 100% local, 50+ languages.

The curated verdict

Same 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.

cocoindex-codetokensave
Stars2.5k460
Forks20341
LanguagePythonRust
LicenseApache-2.0MIT
Last activity4 days ago2 days ago
Topicscoding, localcoding, local
Curated connections38

cocoindex-code — the curator's take

The lowest-friction entry in the code-context-server category: one pipx install, zero config, and the [full] variant ships local embeddings so there's no API key before first search. AST-aware chunking plus the CocoIndex engine underneath means the index stays fresh incrementally instead of rebuilding. Integrates as a skill or MCP with Claude Code, Codex, Cursor. NOT the deepest graph: it's semantic search, not call-graph analysis — no callers/blast-radius queries (that's TokenSave or codegraph-mcp territory) — and the slim install quietly requires a cloud embedding key while [full] costs ~1GB of torch.

tokensave — the curator's take

Use it to stop agents burning tokens on grep/glob/read exploration: one MCP call returns the symbols, relationships and snippets a task needs, and it's local (libSQL, no cloud). Broad reach — 50+ languages, 12+ agent integrations. NOT worth it on small repos where a couple of greps suffice, and it's an index you must keep fresh (re-index on change) — a stale graph misleads the agent. 80+ tools is a lot of surface; most tasks touch a handful.