MCP Secret Scrub

Name: MCP Secret Scrub
Author: sudo-ai-git

by sudo-ai-gitversion 1.0.0i★ –iRuns on your computer

Registry nameio.github.sudo-ai-git/mcp-secret-scrub

Install

Overview

Description from the maker (original English)

Deterministic no-LLM MCP server that scrubs secrets before they reach an agent. Never leaks values.

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: Search & AI memory

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": {
    "secret-scrub": {
      "command": "uvx",
      "args": [
        "mcp-secret-scrub"
      ]
    }
  }
}

Run this in your terminal

claude mcp add secret-scrub -- uvx mcp-secret-scrub

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "secret-scrub": {
      "command": "uvx",
      "args": [
        "mcp-secret-scrub"
      ]
    }
  }
}

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": {
    "secret-scrub": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "mcp-secret-scrub"
      ]
    }
  }
}

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 sudo-ai-git, 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 Search & AI memoryi

More stars than 0% of the other 7286 servers in this category
Published to the registry more recently than 34% of the other 7286 servers in this category
Basic checks equal to or better than 100% of the other 7286 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 MCP Secret Scrub 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 (1.0.0) reached the registry 2 months 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: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated yesterday

Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 21 days ago

Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month

Install

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.

mcp-secret-scrub

mcp-name: io.github.sudo-ai-git/mcp-secret-scrub

Deterministic, no-LLM MCP server that scrubs secrets from text, logs, and transcripts before they enter agent context — and never leaks the value.

No LLM. No network. Pure structural detection. MIT. Crown-jewel-free.

The problem it solves

Before you hand raw text to an agent (or store it, or pass it to a tool), you often don't know whether it contains a live secret. Platform scrubbers miss patterns all the time — a private key, an nvapi- token, a github_pat_ token, an api_key= assignment mid-log. If that text reaches an LLM context or a persisted transcript, the secret is effectively exfiltrated.

This server answers, deterministically:

*Which secrets are in this text, and can you redact them safely before it

goes anywhere?*

Detection coverage (deterministic profiles)

family	examples
AI provider keys	`sk-proj-…`, `sk-ant-api…`, `sk-or-v1-…`, `sk-…`, `nvapi-…`
Cloud / GitHub	`AKIA…`, `aws_secret_access_key=`, `ghp_…`, `gho_…`, `ghu_…`, `ghs_…`, `ghr_…`, `github_pat_…`
Identity / auth	JWTs (`eyJ…`), PEM private keys, `Bearer …`, `Basic …`, OAuth client secrets
Assignments	`api_key=`, `token=`, `secret=`, `password=`, `client_secret=`, `webhook_secret=`
Endpoints / DSNs	Discord webhooks, Slack `xox…`, SQL/Redis/Mongo/AMQP connection strings

The scan never returns the secret value — only its type, count, and position. That is a hard safety contract, enforced by test.

Tools (MCP)

tool	purpose
`scrub_text(text, mode, keep_label)`	redact / mask / hash secrets; returns scrubbed text (never the value)
`scan_text(text)`	detect which secret types are present (no mutation)
`report_full(text)`	scan + redact in one call, scrubbed preview + findings
`secret_profiles()`	list all supported detection profiles

Modes:

`redact` (default) → [REDACTED:TYPE]
`mask` → shows first 4 + last 2 chars
`hash` → deterministic SHA-256 prefix (reproducible across calls)

Quick start (stdio)

pip install mcp-secret-scrub

mcp-secret-scrub # stdio (default)

Or via uv/pipx for an installable console entry:

pipx install mcp-secret-scrub

MCP client config:

{ "mcpServers": {

"secret-scrub": { "command": "mcp-secret-scrub" } }}

Streamable HTTP (remote / Smithery-publishable)

python3 mcp_server.py --http --port 8138   # serves on http://<host>:8138/mcp/

Determinism & safety guarantees

Deterministic: same input → identical output in every mode, every call.
Never leaks: scan_text and scrub_text never emit the original token; _deterministic_hash is SHA-256 (no salt) so output is reproducible.
No LLM, no network: pure regex + reachable structure detection.
Input-safe: non-string input returns a clean error, not a traceback.

Verification

python3 test_detector.py — 14/14 core checks (detection, redaction, determinism, no-leak contract, benign/unicode/empty input, bad-mode)
python3 test_e2e.py — drives the real MCP stdio transport and asserts the secret does NOT cross the wire

License & provenance

MIT. Part of the sudo-ai-git deterministic no-LLM agent-trust MCP family (mcp-skill-sec · mcp-verify-claim · mcp-benchmark-hygiene · mcp-secret-scrub).

MCP Secret Scrub

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 Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

mcp-secret-scrub

The problem it solves

Detection coverage (deterministic profiles)

Tools (MCP)

Quick start (stdio)

Streamable HTTP (remote / Smithery-publishable)

Determinism & safety guarantees

Verification

License & provenance