Lexaudit

Name: Lexaudit
Author: nareyko

by nareykoversion 0.3.1i★ –iRuns on your computer

Registry nameio.github.nareyko/lexaudit

Install

Overview

Description from the maker (original English)

Locale vocabulary audit (calques, inventeds, foreign slips). Local CLI via stdio — no hosted API.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "lexaudit": {
      "command": "uvx",
      "args": [
        "lexaudit"
      ]
    }
  }
}

Run this in your terminal

claude mcp add lexaudit -- uvx lexaudit

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "lexaudit": {
      "command": "uvx",
      "args": [
        "lexaudit"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "lexaudit": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "lexaudit"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account nareyko, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 32696 servers in this category
Published to the registry more recently than 82% of the other 32696 servers in this category
Basic checks equal to or better than 100% of the other 32696 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Lexaudit safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.3.1) reached the registry 8 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, LexPact UK Contracts

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

lexaudit

Finds odd, wrong or copied-from-another-language words in your texts, and tells you which pages to fix first.

In plain words

You write or translate articles, courses or documentation. A normal spellchecker shouts about every brand name, abbreviation and long German word, and still misses the words that really hurt: a word copied from another language ("calque"), a real word used with the wrong meaning ("false friend"), or a word someone invented.

lexaudit reads your files, ignores the harmless things, and gives you a short ranked list: "look at this page first." It runs on an ordinary laptop in about a second. No graphics card, no internet, no account.

It only reports. It never changes your texts.

Unknown terms? See the glossary. 0.3.0 prep and publish path: docs/p1-INDEX.md.

Languages: English (en), German (de), Spanish (es), Polish (pl), Russian (ru), Swedish (sv), Ukrainian (uk)
Hardware: CPU only
Author: Vadim Nareyko (github.com/nareyko, Founder at Arviser Sp. z o.o.)
License: dual MIT package and AGPL-3.0-or-later hosted SaaS (details)

Try it in 30 seconds

pipx run lexaudit audit --path . --locale en --check

or: uvx lexaudit audit --path . --locale en --check

Missing spelling dictionaries download automatically into your user cache. No GPU. No config file required. Exit code 1 means confirmed calques or invented words remain.

Optional helpers: lexaudit doctor, lexaudit fetch-dicts, lexaudit init.

Check a file or a whole project

# One file or folder, no settings file needed

uv run lexaudit audit --path ./README.md --locale en

Or create starter settings first, then check everything

uv run lexaudit init uv run lexaudit audit --locale en

Open the report

The reports are in the output folder, one subfolder per language. Start with queue.md:

| score | unique_suspects | path | top_words |

|---|---|---|---| | 12.0 | 2 | docs/en/en-04-defect-known-calques.md | orientir surveyness | | 6.0 | 1 | docs/en/en-05-defect-false-friend.md | denseness | | 1.6 | 2 | docs/en/en-03-clean-unseen-jargon.md | vinylester haulout |

A higher score means "look here first". top_words shows the words behind the score.

Ask why a word was flagged

uv run lexaudit explain orientir --locale en

word: orientir (normalized: orientir, locale: en)

status: calque (tier: confirmed) reason: loan-calque-orientir | detectors: calque, hunspell editorial hint: working rule / ballpark / figures - not orientir

Reproduce our test results

uv run lexaudit audit --config examples/synthetic-demo/lexaudit.config.yaml

Then open tmp/synthetic-demo-out/ /queue.md.

How good is it? An honest answer

We built a 42-page test set in all 7 languages: 21 clean technical pages and 21 pages with planted problems. Some problems are known to the rules, some are brand new words the rules have never seen. Details: docs/synthetic-benchmark.md.

Setup	Bad page in top 2	Bad page in top 3	Recall@2	Recall@3	MAP (0 to 1, higher is better)	Known problems found	Brand-new neologisms found	Combined planted problems	Clean-page FP / 1k tokens	Time
A. Plain spellchecker	0.0%	23.8%	0.0%	23.8%	0.389	0.0% (0/26)	0.0% (0/7)	0.0% (0/33)	81.2	0.48 s
B. Plus your word lists	7.1%	23.8%	4.8%	23.8%	0.421	0.0% (0/26)	0.0% (0/7)	0.0% (0/33)	47.1	0.56 s
C. Full lexaudit	100.0%	100.0%	66.7%	100.0%	1.000	100.0% (26/26)	100.0% (7/7)	100.0% (33/33)	47.1	2.97 s

What this means:

Pages with known problems come first in every language. The plain spellchecker puts clean pages first.
Known-rule problems: 100.0% (26/26). Unseen single-occurrence neologisms (Zipf + char n-gram / affix-glue): 100.0% (7/7). Combined planted problems (honest fraction): 100.0% (33/33).
With exactly 3 defective pages per locale, Recall@2 is 66.7% when the top-2 slots are both bad (Precision@2 = 100.0%). Precision@3 / Recall@3 are 100.0% (singleton inventeds outrank repeated domain jargon).
Clean-page false positives: 47.1 unique flagged words per 1000 tokens (36 unique FP / 764 tokens).
Domain terms that recur on a page (or sit in H1/title) are tagged domain-term-candidate, nearly zero-weighted in ranking, and listed under Suggested glossary additions.

Documentation

Start with docs/README.md.

Guide	What you learn
Glossary	Every term in plain words
Benchmark	The 42-page test, step by step
Architecture	What goes in, what comes out
Pipeline	The gates every word passes
CLI reference	All commands
Agent workflow	From report to fixed page
Scores and metrics	How pages are scored

More commands

# Re-rank pages, filter by source (docs, academy, model_pack)

uv run lexaudit rank --locale ru --mode weighted --sources=docs

Add every page that contains a known bad word to your to-do list

uv run lexaudit expand-needle --needle orientir --locale all \ --write-queue /abs/path/to/rewrite-queue.md

Optional: ask a language model for a second opinion (your own endpoint)

uv run lexaudit label --locale ru --top-pages 20 --top-words 50 --tiers likely,weak --profile cpu

Compare two runs

uv run lexaudit diff --baseline .../report.json --current .../report.json --out /tmp/diff.json

For contributors

Setup and checks:

uv sync --extra dev

uv run ruff check . && uv run ruff format --check . uv run mypy --strict src/ uv run pytest uv run python scripts/crap_report.py uv run mutmut run && uv run python scripts/check_mutation_score.py --min-percent 80 uv build

Test layers: unit and integration tests (branch coverage 80% or more), the 7-language benchmark, property-based fuzzing (Hypothesis), golden regression with a read-only check of your files, JSON Schema contract, complexity gate (CRAP), mutation testing (kill rate 80% or more).

Pictures in docs/images are generated from code: run python scripts/render_diagrams.py (needs Inkscape and Pillow). Never edit the JPG files by hand.

License

What	License
PyPI / this repo’s code (CLI, library, YAML rules, packs)	[MIT](LICENSE) — use in products and private SaaS is fine under MIT
Intended future hosted multi-tenant network service (not shipped here)	Policy text: AGPL-3.0-or-later — not a second license on the MIT wheel
Benchmark corpora & fetched spelling dictionaries	LICENSE-THIRD-PARTY.md + upstream `*.license.txt`

Full wording: docs/licensing.md. Adding rules: docs/contributing-rules.md.

Origin and author

Created and maintained by Vadim Nareyko (github.com/nareyko). It grew out of auditing multilingual courses and encyclopedias at FairHelm.

Lexaudit

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

LexPact UK Contracts

README from the maker

lexaudit

In plain words

Try it in 30 seconds

or: uvx lexaudit audit --path . --locale en --check

Check a file or a whole project

Or create starter settings first, then check everything

Open the report

Ask why a word was flagged

Reproduce our test results

How good is it? An honest answer

Documentation

More commands

Add every page that contains a known bad word to your to-do list

Optional: ask a language model for a second opinion (your own endpoint)

Compare two runs

For contributors

License

Origin and author