Memtrace Public

Memtrace's strongest argument is that it doesn't try to be a general agent-memory tool. It reasons over call graphs, dependencies, cross-repo API paths, test coverage and blast radius — structural facts that conversation summaries can't represent. When an agent asks 'what breaks if we change auth?', Memtrace is designed to answer with 12 callers across 2 services and three covering tests, checked against the code graph rather than a transcript. That's a different product from the summarization tools. The second argument is token economics. Memtrace's published benchmark claims its target file ranked first 96.6% of the time across 1,000 exact-symbol queries, with 84.7% fewer file-content tokens in a typical session and 202 response tokens per correct result. These are vendor self-reports, not third-party measurements, so the honest posture is: promising, directionally consistent with what you'd expect from graph queries replacing raw file reads, and unverified until you run it on your repo. The third argument is deployment. Source analysis runs locally by default; teams can self-host shared MemDB in infrastructure they control; memory and coordination calls don't hit an LLM. For organizations that block sending source to third-party platforms, that combination is often the deciding factor. The v1.2.0 additions — native desktop receipts on Windows, macOS and Linux, plus GPU embedding throughput up to 24x on supported NVIDIA hardware — plus v1.1.5's cross-repo call detection for C#/C++ HTTP clients, gRPC, WebSocket, message queues and Python subprocesses, plus v1.2.8's expanded language coverage (Perl, Zig, SQL, COBOL, Dart, R, Vue, Swift, Nextflow among them) show active development against a specific engineering surface, not a wrapper. Weaknesses. Setup is CLI-driven (npm install -g memtrace) and requires sign-in (Google or GitHub) before it provisions a license; you need to grant coding agents file-write permissions for the workflow to pay off. The ecosystem is young — no large third-party library of tutorials and plugins yet. The changelog ships a nightly channel alongside stable, and a tool that inspects your code graph deeply is a tool you want to keep current. Most importantly, the benefits scale with concurrency: at one agent and one small repo, you're paying setup cost for memory you barely need.