Disclosure: I’m the developer of vexp. Free tier: 2K nodes, 1 repo, no time limit. Pro $19/mo (code PRODUCTHUNT for 1 month free - we just launched on PH). Benchmarked 42 runs on FastAPI (~800 files, Sonnet 4.6). Before writing anything, Claude does: Read file → grep → glob → read another file → grep again → read imports → grep → read tests… averaging 23 tool calls just to orient itself. Built an MCP server that pre-indexes the codebase into a dependency graph (Rust + tree-sitter + SQLite). Claude calls run_pipeline once, gets a ranked context capsule with only the relevant subgraph. 23 tool calls → 2.3. The results I didn’t expect: Cost per task: $0.78 → $0.33 (-58%) Output tokens: 504 → 189 (-63%) Claude literally writes less when it gets better input. The “let me look at this file…” narration disappears entirely Cost variance dropped 24x on refactoring tasks - way more predictable Also has session memory linked to code symbols. What Claude learned yesterday auto-surfaces today. When code changes, linked memories go stale. 100% local, zero cloud. Works with Cursor, Copilot, Windsurf, and 9 other agents too. vexp.dev
- free on the VS Code Marketplace. What does your tool call count look like on large codebases? Curious if 23 is typical or if my setup was particularly bad. submitted by /u/Objective_Law2034
Originally posted by u/Objective_Law2034 on r/ClaudeCode