
argot
io.github.get-tmonierPublished by GitHub account get-tmonierv0.2.127Updated Oct 25, 2026
Read-only context and complete checks against patterns learned from git history. Local; no LLM.
Overview
Argot is a local, read-only MCP server that gives an assistant statistical checks against patterns learned from a repository's own git history.
- What you can do
- Provide read-only context about a fitted repository's learned conventions and history-derived patterns, with evidence behind each finding, so the assistant can explain why a change looks foreign to the repo. Offer hunk-level and complete-changeset checks that flag issues such as unfamiliar imports or callees, rare tokens, broken conventions, superseded patterns, duplicated or misplaced functions, reversed layering, and weakened or deleted tests. Surface findings as review prompts rather than verdicts, leaving the accept-or-reject decision to the user. Fitting the repository itself stays a separate local CLI or skill workflow, not an MCP action.
- When to use it
- Use it when reviewing AI-written or human pull requests in a repository with usable git history and you want the assistant to point out code that is type-correct but stylistically or structurally foreign to that codebase. It is a review aid, not a correctness oracle, so pair it with normal review and tests.
- Requirements
- Runs as a local stdio process, installed via npx from the npm package @tmonier/argot (or a global install). The repository must be fitted first with the local CLI (argot init) and have usable git history and supported source; model-dependent tools need that fitted snapshot. No account, API key, or network access is required; the embedding model ships inside the binary.
Installation
In SourceWeft
- Open argot in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
Lint the rules you never wrote down.
AI writes the code. argot harnesses it with the one thing that can’t
hallucinate: your repo’s own history.
Statistics, not a second LLM. 100% local. It surfaces the divergence — you
decide what to accept.
argot.tmonier.com · Documentation · Evidence · Research log
[One statically-linked Rust binary] [100% local, no cloud, no account] [12 supported languages] [Benchmarked on 36 real repositories]
Start with an audit
argot audit needs no prior Argot fit or configuration. It fits a historical
base in a temporary worktree, then evaluates the surviving base-to-HEAD net
diff. Your working tree is left untouched. It is a review prompt—not a census
of who wrote code, or proof that a finding is a defect.
Windows: powershell -c "irm https://github.com/get-tmonier/argot/releases/latest/download/argot-installer.ps1 | iex".
The npm package is also available as npm install -g @tmonier/argot.
Audit needs usable Git history and supported source. It has no fixed runtime promise. It runs fully offline — the code-embedding model behind the semantic findings ships inside the binary. See Getting started for install and fit details.
If the audit gives you a useful lead, fit the current repository and score the changes you intend to review:
Review and commit the generated argot.toml and .argot/ fit snapshot, then
merge it into the branch future PRs target before adding a CI workflow. Local
tools and CI then use the same learned baseline. CI only reads the base branch
snapshot; it never fits, so the initial snapshot PR must be separate from the
CI-workflow PR. argot status later recommends a local
fit-and-commit refresh only when accepted source, function, or layout surfaces
have materially changed. Commit count and age are not refresh triggers by
default; [fit] refresh-after is available only as an explicit team backstop.
The argot-refresh skill re-audits exclusions, structural paths, and mutes
before fitting, so a reorganized repository does not blindly relearn old scope.
The embedding model itself ships inside the binary. Git stores only the repository-specific learned snapshot—typically a few MB to a few tens of MB—so every clone can reproduce the check without retraining or operating a service.
check reports patterns worth reviewing on the selected changeset; a clean result
does not prove the change correct or fully idiomatic. Read the
Audit,
Init and Fit, and
Check guides for the exact contracts.
What it surfaces
Type checkers ask if it compiles. argot asks if it’s yours. A clean, type-correct, well-reviewed pull request can still be foreign to the repository it lands in. These are the rules argot ships, every one of them learned from your own history rather than configured by hand:
Repositories add their own on top — a TOML manifest plus a sandboxed Rhai
script under .argot/rules/, with working ones to copy in
examples/rules/. No recompilation.
argot is a probabilistic review guardrail, not a correctness oracle. Each finding carries repository evidence. Treat it as a prompt to inspect and make the human decision explicit—never as proof that the code is wrong.
Choose how to run it
The CLI is the complete, explicit changeset check. Other routes have narrower triggers and coverage; none provides a universal acceptance-time check.
Canonical setup and host details: Claude Code, other agents and MCP, and CI and pre-commit.
Evidence and limits
Current public measurements are detector-specific, not a product-wide accuracy or combined-brief claim. The approved claim manifest records:
- visible foreign-symbol fixtures: 620/637 — 97.3% across 36 corpora and 12 languages;
- reinvention fixtures: 545/584 — 93.3% across 31 corpora and 11 languages;
- placement transplants: 12,899/13,456 — 95.9% across the 22 evaluable corpora and 11 languages (the other nine abstain because their layouts have no separable architecture);
- layering fixtures: 264/272 — 97.1% across 25 corpora and 12 languages;
- test-integrity fixtures: 154/164 — 93.9% across 23 corpora and 12 languages.
A catch rate means little without the noise it costs, so both are published. On the same 36 corpora, the voice detectors flag 0.25% of ordinary accepted edits — and 0.00% of the hunks in newly added files, where a repository has the least to say about what belongs.
Each number has a distinct corpus, denominator, and qualifier. The combined briefing/noise result and ordinary-repository timing are not yet measured public claims. See the benchmark methodology and sources.
Argot ships adapters for 12 languages. The five tested release targets are macOS arm64/x64, Linux x64/arm64, and Windows x64. The local analysis path uses statistical, graph, scripted, and embedding evidence; no generative or opinion-forming model decides a finding.
Fit health matters. A repository with shallow, generated, vendored, or otherwise unsuitable history may not produce a useful model. Argot is also least reliable for an incorrect choice made entirely with familiar vocabulary, masked prose, and code outside the selected range. Read Limitations before relying on a specific detector.
Reproducible authored proof
This is an authored fixture, not a wild-case corpus. Its pinned command, version, receipts, checksums, regeneration procedure, and the visual’s non-byte-stable GIF qualification are documented in the proof receipt. The image is a reproducible companion to the auditable Markdown receipt.
Privacy and open source
Argot analyzes source, history, and findings locally. The individual local core
is free, MIT-licensed open source, and requires no account or cloud service.
Argot has no default telemetry and does not upload source code. No analysis it
performs needs a network at all — the code-embedding model behind the semantic
findings is compiled into the binary. It can still use network paths for
update/version checks, release downloads, or an explicitly configured
review/update/CI integration. Set ARGOT_OFFLINE=1 to prevent network use;
nothing analytical is lost.
Read the complete privacy and security boundary, security policy, and MIT license.
Contribute
Contributions are welcome. Start with CONTRIBUTING.md, then see the product strategy for the maintained decision record and research log for evidence.
Acknowledgements
Every number argot publishes is measured against the real history of 36 open-source projects, across the twelve supported languages — fastapi, rich, faker, saleor, wagtail, scrapy, hono, ink, faker-js, excalidraw, outline, express, commander, eslint, gh-cli, hugo, ripgrep, bat, guava, junit5, powershell, jellyfin, redis, curl, rocksdb, fmt, homebrew, rubocop, laravel, composer, castle-engine, mORMot2, uos, ideU, MSEide/MSEgui, and dagster.
The benchmark would not exist without them, and we are grateful to their
maintainers and contributors. Argot vendors and redistributes none of their
code: the harness clones each repository at a pinned SHA, reads its history
locally, and ships nothing from it. Each project remains under its own license,
held by its own authors. Full list with links, and what argot does commit:
benchmarks/README.md.
argot does redistribute one thing. The model behind redundant and misplaced
is a 15.6M-parameter static table distilled from
jina-embeddings-v2-base-code
(Jina AI, Apache-2.0) using the
model2vec technique (MinishLab, MIT).
Its weights are compiled into the binary and redistributed under Apache-2.0;
full terms in NOTICE. argot is not affiliated with either project.
Source: README.md at commit 254a7ef
Tools
0Version history
1- v0.2.127LatestSep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts