gortex vs tokensave
Code-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. — 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.
Same 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.
| gortex | tokensave | |
|---|---|---|
| Stars | 1.1k | 525 |
| Forks | 98 | 54 |
| Language | Go | Rust |
| License | Apache-2.0 | MIT |
| Last activity | yesterday | 3 days ago |
| Topics | code-intel, local | code-intel, local |
| Curated connections | 3 | 12 |
gortex — the curator's take
The coverage play on this shelf: 257 grammars, cross-repo and cross-SERVICE edges (HTTP routes, contracts) with a provenance/confidence tier the single-repo tools don't attempt, and one install that configures 19 coding agents. When NOT: 175 MCP tools is a context bill of its own — prune the toolset or your agent pays the index's price in schema tokens; benchmarks are self-published; and if you want memory as plain files, this is the opposite philosophy.
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.