jevgrep vs tokensave
Find code by asking what it does: `jg` uses the Jev decision model to judge folders, files and declarations, returning relevant files plus verbatim excerpts for coding agents. CLI + skill. — 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.
Both cut the tokens an agent spends locating code; tokensave pre-indexes a semantic graph agents query over MCP, jevgrep stays index-free and returns source excerpts per natural-language question.
| jevgrep | tokensave | |
|---|---|---|
| Stars | 2.6k | 657 |
| Forks | 189 | 67 |
| Language | TypeScript | Rust |
| License | MIT | MIT |
| Last activity | 9 days ago | 4 days ago |
| Topics | code-intel, coding | code-intel, local |
| Curated connections | 3 | 17 |
jevgrep — the curator's take
Use it when your agent lands in an unfamiliar repo and burns turns grepping for where a behavior lives — no index to build, and measured ~26% lower total cost at the same solve rate on its own 10-task SWE-bench run. Skip it when you already know the symbol or path (plain `rg` wins), or when you want zero per-query spend: every search is a paid Jev call through Vercel AI Gateway, TypeSafe, OpenRouter or a compatible endpoint. Install the skill too, or agents won't call it.
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.