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Releaseguard

by RudrenduPaulversion 0.1.2i★ –iRuns on your computer
Registry nameio.github.RudrenduPaul/releaseguard

Install

Overview

Description from the maker (original English)

Scans datasets/models for PII/secrets, redacts, and packages a public-release bundle via MCP.

PopNx MCP’s three pillars

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

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?

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": {
    "releaseguard": {
      "command": "uvx",
      "args": [
        "releaseguard-cli",
        "releaseguard",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add releaseguard -- uvx releaseguard-cli releaseguard mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "releaseguard": {
      "command": "uvx",
      "args": [
        "releaseguard-cli",
        "releaseguard",
        "mcp"
      ]
    }
  }
}

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": {
    "releaseguard": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "releaseguard-cli",
        "releaseguard",
        "mcp"
      ]
    }
  }
}

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 RudrenduPaul, 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 32700 servers in this category
  • Published to the registry more recently than 22% of the other 32700 servers in this category
  • Basic checks equal to or better than 100% of the other 32700 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 Releaseguard 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 (0.1.2) reached the registry 3 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: Spec Driven Development, Remote Desktop Commander, Agent Data Tools: Utilities

Alternatives

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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.

ReleaseGuard

Install • Quickstart • CLI reference • Library API • Comparison • FAQ

Scan a dataset or model directory for PII and secrets with [Presidio](https://github.com/data-privacy-stack/presidio), redact what you find, and generate a public-release bundle, a Hugging Face dataset/model card plus an EU AI Act Art. 53(1)(d) training-data summary, in one command.

ReleaseGuard is not a PII detector. It's the glue between "I have a dataset I want to publish" and "I have a sanitized bundle with the paperwork already drafted." Detection is entirely Presidio's, an actively maintained open-source project with 10,000+ GitHub stars. ReleaseGuard chains Presidio's scan straight into redaction and into the two documents almost every public dataset/model release actually needs, instead of you writing a script to do it yourself.

Install

pip install releaseguard-cli

python -m spacy download en_core_web_sm # Presidio's default NLP model (~13 MB, one-time)

npm launcher (thin wrapper around the PyPI package, see "Why two registries" in FAQ)

npx releaseguard-cli --help

en_core_web_sm is spaCy's small English model and Presidio's own quickstart default. For higher-accuracy detection, install the larger model instead and pass --spacy-model:

python -m spacy download en_core_web_lg   # ~400 MB, Presidio's recommendation for production

releaseguard scan ./data --spacy-model en_core_web_lg

Quickstart

This is a real, unedited run against a two-row sample CSV, not a mockup:

$ releaseguard scan dataset --score-threshold 0.4

Scanned 1 file(s) under dataset Total findings: 7

entity type count URL 3 PERSON 2 EMAIL_ADDRESS 2

That URL: 3 line is a real Presidio quirk worth calling out rather than hiding: its regex-based URL recognizer also fires on the domain portion of an email address (example.com inside alice.rivera@example.com), so email-heavy text double-counts as both EMAIL_ADDRESS and URL. This is Presidio's own recognizer behavior, unmodified, and it's worth noting entity counts can shift slightly between Presidio/spaCy versions since detection is NLP-based, not a fixed lookup table (this run used presidio-analyzer 2.2.364 with en_core_web_sm 3.8.0). Filter it out with --entities if you only care about email addresses:

releaseguard scan dataset --entities EMAIL_ADDRESS,PERSON,PHONE_NUMBER

Redact, then package a release bundle in one command:

$ releaseguard package dataset --output bundle --score-threshold 0.4

Release bundle written to bundle dataset card: bundle/README-dataset-card.md EU AI Act Art. 53(1)(d) summary: bundle/eu-ai-act-training-summary.md redacted source: bundle-redacted-source

bundle/eu-ai-act-training-summary.md opens like this, real scan counts filled in, everything else left as an explicit placeholder for a human to complete:

# Training Data Summary (EU AI Act Art. 53(1)(d))

_Draft generated by ReleaseGuard... Based on the European Commission's training-data-summary template, published 2025-07-24. This covers the narrow, currently-binding categorical-summary requirement only -- it is not a claim of full training-data disclosure._

4. Personal Data and PII Handling (from ReleaseGuard scan)

A Presidio-backed scan (detector: presidio) covered 1 file(s) under dataset.

PII/secret category detectedOccurrences
EMAIL_ADDRESS2
PERSON2
URL3

--json on every command switches to machine-readable output for scripts and agents.

Quick summary

  • Use it for: turning a Presidio scan into a redacted copy plus a dataset/model card and an EU AI Act Art. 53(1)(d) training-data summary, from one command instead of three separate tools and a hand-written template
  • What it's not: a PII detector of its own, or a claim of "total transparency"/full training-data disclosure compliance. See What ReleaseGuard is not
  • Runs entirely local. No dataset content, scan results, or redacted output is ever sent to a remote service.

CLI reference

$ releaseguard --help

Usage: releaseguard [OPTIONS] COMMAND [ARGS]...

Scan, redact, and package a dataset/model directory for public release.

ReleaseGuard is a packaging layer on top of Presidio (originally a Microsoft project, now maintained by data-privacy-stack) -- it does not detect PII independently of Presidio. See the README's "What ReleaseGuard is not" section.

Options: --version Show the version and exit. --help Show this message and exit.

Commands: mcp Start an MCP server exposing scan/redact/package as agent tools. package Scan PATH, optionally redact it, and generate a release bundle... redact Scan PATH and write a redacted copy to --output. scan Scan PATH (a file or directory) for PII and secrets using...

CommandPurpose
scan PATHScans a file or directory (CSV, JSON/JSONL, plain text) with Presidio. --entities, --score-threshold, --spacy-model, --json.
redact PATH --output DIRScans, then writes a redacted copy to DIR. Never touches PATH. `--strategy mask\hash\remove, --overwrite`.
package PATH --output DIRScans (and by default redacts first), then writes a Hugging Face dataset/model card plus the EU AI Act Art. 53(1)(d) summary to DIR. `--kind dataset\model\both, --redact-first/--no-redact-first`.
mcpStarts an MCP server (stdio) exposing scan_directory_tool, redact_directory_tool, package_release_tool. Requires pip install "releaseguard-cli[mcp]" on Python 3.10+.

Every command supports --json. Full flag reference: releaseguard --help.

Library API

from releaseguard.detectors import get_detector

from releaseguard.scanner import scan_directory from releaseguard.redactor import redact_directory from releaseguard.packager import build_release_bundle from releaseguard.types import RedactionStrategy

detector = get_detector("presidio", score_threshold=0.4) scan_result = scan_directory("dataset/", detector)

redaction_result = redact_directory( scan_result, "dataset-redacted/", strategy=RedactionStrategy.MASK )

bundle = build_release_bundle( scan_result, "bundle/", redaction_result=redaction_result, source_kind="dataset" ) print(bundle.eu_ai_act_summary_path)

PIIDetector (releaseguard.detectors.base) and FileReader (releaseguard.readers.base) are the two extension points. Presidio is currently the only detector shipped; CSV, JSON/JSONL, and plain text are currently the three readers shipped. Both are registries, not hardcoded calls, specifically so a new format or a second detection backend is a scoped addition later. See CONTRIBUTING.md.

MCP Server

ReleaseGuard ships a Model Context Protocol server so an AI agent (Claude, Cursor, or any MCP-compatible client) can scan, redact, and package a dataset or model directory directly, without a human invoking the CLI by hand.

Install the extra:

pip install "releaseguard-cli[mcp]"

Start it directly with the mcp subcommand:

releaseguard mcp

Add it to your MCP client's config (for Claude Desktop, claude_desktop_config.json). The server is started via a subcommand of the published releaseguard console script, not a separate console script of its own:

{

"mcpServers": { "releaseguard": { "command": "uvx", "args": ["--from", "releaseguard-cli", "releaseguard", "mcp"] } } }

Transport is stdio, so there is nothing to host: the MCP client spawns the server as a local subprocess. Source: src/releaseguard/mcp_server.py.

The server exposes three tools, each returning the same JSON shape as the matching CLI --json output:

ToolPurpose
scan_directory_tool(path, spacy_model=None, score_threshold=0.35)Scan a directory for PII and secrets with Presidio.
redact_directory_tool(path, output, strategy="mask", overwrite=False)Scan, then write a redacted copy to output. Never mutates path. strategy is "mask", "hash", or "remove".
package_release_tool(path, output, kind="dataset", redact_first=True, strategy="mask")Scan, optionally redact, and write a release bundle (dataset/model card plus the EU AI Act Art. 53(1)(d) summary) to output.

A real example call:

scan_directory_tool(path="./dataset", score_threshold=0.4)

-> {"files_scanned": 1, "root_path": "./dataset", "findings": [...], "entity_counts": {"URL": 3, "PERSON": 2, "EMAIL_ADDRESS": 2}}

Every tool checks that path exists before doing anything else and returns a structured error, {"error": "Path ' ' does not exist.", "error_type": "PathNotFound"}, instead of a silent, misleading "0 files scanned" success result. Earlier versions of this server skipped that check and let a bad path slip straight into scan_directory, which returned a false success instead of an error; every tool handler is also now wrapped so an unexpected exception comes back as {"error": ..., "error_type": ...} rather than crashing the server. A .well-known/agent.json manifest is shipped at the repo root for A2A-style discovery, listing both the CLI and MCP interfaces and the packages that provide them.

Comparison

ReleaseGuardPresidiohuggingface_hub card toolingpii-lib
Detects PII/secretsNo, wraps PresidioYes (its own job)NoYes (regex + NER, code-training-data scoped)
Redacts detected entitiesYes (via presidio-anonymizer)Yes (library-level)NoYes
Generates a Hugging Face dataset/model cardYes, from real scan resultsNoYes (manual fields, no scan integration)No
Generates an EU AI Act Art. 53(1)(d) summaryYes, from real scan resultsNoNoNo
One command, scan through release bundleYesNo (library only, you write the glue)No (library only)No
GitHub stars (checked 2026-08)New in 2026~10,300~3,80016

Star counts checked live against the GitHub API on 2026-08-03: data-privacy-stack/presidio (originally microsoft/presidio; the project moved organizations, same codebase), huggingface/huggingface_hub, [bigcode-pro

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