Deterministic no-LLM MCP server that scrubs secrets from text/logs before agent context. Redact/mask/hash, never leaks the value.
- ✓Open-source license (MIT)
- ✓Actively maintained (<30d)
- ✓Clear description
- ✓Topics declared
- ✓Documented (README)
claude mcp add mcp-secret-scrub -- python -m mcp-secret-scrub{
"mcpServers": {
"mcp-secret-scrub": {
"command": "python",
"args": ["-m", "mcp-secret-scrub"]
}
}
}MCP Servers overview
# 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)
```bash
pip install mcp-secret-scrub
mcp-secret-scrub # stdio (default)
```
Or via uv/pipx for an installable console entry:
```bash
pipx install mcp-secret-scrub
```
MCP client config:
```json
{ "mcpServers": {
"secret-scrub": { "command": "mcp-secret-scrub" }
}}
```
## Streamable HTTP (remote / Smithery-publishable)
```bash
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`).
What people ask about mcp-secret-scrub
What is sudo-ai-git/mcp-secret-scrub?
+
sudo-ai-git/mcp-secret-scrub is mcp servers for the Claude AI ecosystem. Deterministic no-LLM MCP server that scrubs secrets from text/logs before agent context. Redact/mask/hash, never leaks the value. It has 0 GitHub stars and its last recorded update is dated 2026-08-28.
How do I install mcp-secret-scrub?
+
You can install mcp-secret-scrub by cloning the repository (https://github.com/sudo-ai-git/mcp-secret-scrub) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is sudo-ai-git/mcp-secret-scrub safe to use?
+
Our security agent has analyzed sudo-ai-git/mcp-secret-scrub and assigned a Trust Score of 95/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.
Who maintains sudo-ai-git/mcp-secret-scrub?
+
sudo-ai-git/mcp-secret-scrub is maintained by sudo-ai-git. The last recorded GitHub activity is dated 2026-08-28, with 0 open issues.
Are there alternatives to mcp-secret-scrub?
+
Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.
Deploy mcp-secret-scrub to your cloud
Ship this repo to production in minutes. Each platform spins up its own environment with editable env vars.
Maintain this repo? Add a badge to your README
Drop the badge into your GitHub README to show it's tracked on ClaudeWave. Each badge links back to this page and reflects the live Trust Score.
[](https://claudewave.com/repo/sudo-ai-git-mcp-secret-scrub)<a href="https://claudewave.com/repo/sudo-ai-git-mcp-secret-scrub"><img src="https://claudewave.com/api/badge/sudo-ai-git-mcp-secret-scrub" alt="Featured on ClaudeWave: sudo-ai-git/mcp-secret-scrub" width="320" height="64" /></a>More MCP Servers
Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
An open-source AI agent that brings the power of Gemini directly into your terminal.
Real-time global intelligence dashboard. AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface
The fastest path to AI-powered full stack observability, even for lean teams.
🕷️ An adaptive Web Scraping framework that handles everything from a single request to a full-scale crawl!