Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Scans datasets/models for PII/secrets, redacts, and packages a public-release bundle via MCP.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"releaseguard": {
"command": "uvx",
"args": [
"releaseguard-cli",
"releaseguard",
"mcp"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add releaseguard -- uvx releaseguard-cli releaseguard mcpIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"releaseguard": {
"command": "uvx",
"args": [
"releaseguard-cli",
"releaseguard",
"mcp"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"releaseguard": {
"type": "stdio",
"command": "uvx",
"args": [
"releaseguard-cli",
"releaseguard",
"mcp"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto RudrenduPaul bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.1.2) kam vor 3 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Python (uv) auf deinem Computer.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, FlyDocs
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Spec-driven development workflow: your agent works issues, sessions and the status lifecycle.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
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.
pip install releaseguard-cli
python -m spacy download en_core_web_sm # Presidio's default NLP model (~13 MB, one-time)
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
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._
A Presidio-backed scan (detector: presidio) covered 1 file(s) under dataset.
| PII/secret category detected | Occurrences |
|---|---|
EMAIL_ADDRESS | 2 |
PERSON | 2 |
URL | 3 |
--json on every command switches to machine-readable output for scripts and agents.
$ 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...
| Command | Purpose | ||
|---|---|---|---|
scan PATH | Scans a file or directory (CSV, JSON/JSONL, plain text) with Presidio. --entities, --score-threshold, --spacy-model, --json. | ||
redact PATH --output DIR | Scans, then writes a redacted copy to DIR. Never touches PATH. `--strategy mask\ | hash\ | remove, --overwrite`. |
package PATH --output DIR | Scans (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`. |
mcp | Starts 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.
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.
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:
| Tool | Purpose |
|---|---|
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.
| ReleaseGuard | Presidio | huggingface_hub card tooling | pii-lib | |
|---|---|---|---|---|
| Detects PII/secrets | No, wraps Presidio | Yes (its own job) | No | Yes (regex + NER, code-training-data scoped) |
| Redacts detected entities | Yes (via presidio-anonymizer) | Yes (library-level) | No | Yes |
| Generates a Hugging Face dataset/model card | Yes, from real scan results | No | Yes (manual fields, no scan integration) | No |
| Generates an EU AI Act Art. 53(1)(d) summary | Yes, from real scan results | No | No | No |
| One command, scan through release bundle | Yes | No (library only, you write the glue) | No (library only) | No |
| GitHub stars (checked 2026-08) | New in 2026 | ~10,300 | ~3,800 | 16 |
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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