Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Safe to run? Will it work? Complete? An A-F grade for any repo, plus a verify loop. Never runs it.
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.
CODE_GUARDIAN_LLM_URL, CODE_GUARDIAN_LLM_MODELDu 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": {
"code-guardian": {
"command": "uvx",
"args": [
"code-guardian-mcp",
"mcp"
],
"env": {
"CODE_GUARDIAN_LLM_URL": "your-value",
"CODE_GUARDIAN_LLM_MODEL": "your-value"
}
}
}
}Führe das in deinem Terminal aus
claude mcp add code-guardian --env CODE_GUARDIAN_LLM_URL=your-value --env CODE_GUARDIAN_LLM_MODEL=your-value -- uvx code-guardian-mcp mcpTrag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"code-guardian": {
"command": "uvx",
"args": [
"code-guardian-mcp",
"mcp"
],
"env": {
"CODE_GUARDIAN_LLM_URL": "your-value",
"CODE_GUARDIAN_LLM_MODEL": "your-value"
}
}
}
}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": {
"code-guardian": {
"type": "stdio",
"command": "uvx",
"args": [
"code-guardian-mcp",
"mcp"
],
"env": {
"CODE_GUARDIAN_LLM_URL": "your-value",
"CODE_GUARDIAN_LLM_MODEL": "your-value"
}
}
}
}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.
CODE_GUARDIAN_LLM_URL envCODE_GUARDIAN_LLM_MODEL envDiese 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 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto LuminariSoftwares 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 (0.6.0) kam gestern 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, Symantec Cloud DLP AIops
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.
Governed Symantec Cloud DLP — 14 MCP tools, read-only with audit.
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.
Status: active development -- changelog
mcp-name: io.github.LuminariSoftwares/code-guardian
0 FAIL findings on 8 of 8 clean, well-known repositories, scanned without running them.
A deterministic A-F grade for any repo -- is it safe to run, will it work, is it complete -- for people about to run code they did not write.
From a clean Python 3.11+ environment (no other dependencies):
pip install code-guardian-mcp
code-guardian scan /home/user/project # the grade, every finding with file:line; exit 0, 1 or 3 code-guardian plan /home/user/project --top 3 # the three fixes worth the most Overall points
Success looks like a first line code-guardian 0.6.0 scan of , then a status: COMPLETE line and four score lines. On a one-file project it takes well under a second. To give the same tools to an AI client, add the MCP server (see MCP server for Claude Desktop and other clients):
claude mcp add code-guardian -- uvx code-guardian-mcp mcp
Run on 2026-11-05 from a fresh clone of the v0.6.0 tag, with code-guardian-mcp==0.6.0 installed from PyPI:
python tools/calibrate.py
Result: 0 FAIL findings on 8 pinned repositories (5 well-known Python projects and 3 sibling guardians).
python -m pytest -q
1386 passed, 82 skipped in 147.56s (0:02:27)
Caveat: this is static analysis. A grade A is "nothing the scanners recognise", not "proven safe". Python is analysed in full, JavaScript and TypeScript at token level, and every other language gets the secret scan and the repo-hygiene checks only.
Before you run a repository you did not write, or merge a change an AI assistant made, you want to know whether it is dangerous, whether it is broken and what is missing. code-guardian answers that from the source alone, in one command that tells you three things about any repo without running it:
Each is a score out of 100 (higher is better), combined into an Overall score and an A–F grade. Scores come only from deterministic checks with fixed weights: same repo, same version, same output, every time. On top of that:
It parses the code (ast for Python; a small lexer for JavaScript and TypeScript; json, tomllib and configparser for manifests; regular expressions for secrets) and never executes, imports or installs it. A scan makes no network calls. Python 3.11+, standard library only.
One of four free, MIT-licensed guardians for people running local models, each answering one question from the outside: tool-guardian (what do my tools cost the window?), context-guardian (will this session hit the limit?), stack-guardian (is my stack healthy?), code-guardian (is this code safe to run?).
Who it is for. Anyone running local AI models, or code an AI assistant wrote, on their own machine: you cloned a repository, or an assistant just rewrote a module, and you want a verdict before you run it. It is the fourth of four free, MIT-licensed guardians, each answering one question about a local setup from the outside:
| guardian | the question it answers |
|---|---|
| code-guardian (this one) | is this codebase safe to run, will it work, does it have what it needs? |
| stack-guardian | is my home AI stack healthy — nodes, loaded models, GPUs, tailnet peers? |
| context-guardian | will this session hit the model's context limit and die? |
| tool-guardian | what are my MCP servers' tool definitions costing the context window? |
Install it as `code-guardian-mcp`; code-guardian on PyPI is an unrelated project by someone else. You get a CLI, a GitHub Action, a pre-commit hook and an MCP server. The MCP side is a hand-written stdio server speaking MCP protocol 2024-11-05 — no SDK, no dependencies (see ADR 0003) — and it is stdio only: to reach it over a network, put an authenticating proxy in front of it rather than exposing the process. One maintainer, best effort: issues and pull requests get a reply when evenings allow, and there is no paid support (CONTRIBUTING.md, SECURITY.md).
Python is analysed in full, JavaScript and TypeScript at token level, and every other language gets the secret scan and the repo-hygiene checks only. Every report prints a coverage: line saying which files were analysed and how, e.g. coverage: 40 Python analysed; 112 JavaScript/TypeScript analysed (token level); 9 .go secret-scan only, and coverage.languages in the JSON gives the same with the checks that ran.
| language | files | depth | what runs |
|---|---|---|---|
| Python | .py | full | every Safe, Works and Complete check, from the parse tree (ast) |
| JavaScript / TypeScript | .js .mjs .cjs .jsx .ts .tsx | tokens | the secret scan, the Safe checks and the Works checks marked JavaScript / TypeScript in the tables below, run on a token list |
| everything else | Go, Rust, shell, .vue, .svelte and the rest | secret scan only | key shapes, manifest and install-hook reading (package.json, setup.py, pyproject.toml, ...) and the Complete checks (licence, README, CI, .env.example) |
What "token level" means. A lexer cuts each JavaScript or TypeScript file into tokens, telling strings, template literals, comments, regular expressions and JSX text from code, so a sink named in a string or a comment is never a finding. It is a lexer, not a parser: a check reads call sites, imports, assignments and object-literal properties off the tokens, one statement deep, and follows nothing between statements or functions. The checks are exec.dynamic, exec.shell, deser.unsafe, net.egress, net.bind_all, tls.off, obfuscation, fs.outside, privacy.pii_log and dom.html_sink (Safe) and works.syntax, works.import_unresolved, works.relative_missing, works.entry_missing and works.tests_missing (Works). Not ported from the Python side: privacy.pii_prompt, works.test_no_assert, works.todo_stub, works.commented_code, works.dead_flag and the orphan (dead code) check; coverage.languages.javascript.not_checked lists them. Nothing is installed, imported or run: no npm, no node.
Generated files. A declaration file (*.d.ts), a minified or bundled file (*.min.js, *.min.mjs, *.bundle.js) and any JavaScript or TypeScript file with a line longer than 2,000 characters in its first 8 KB are counted as generated (files.generated). They get the secret scan and the obfuscation and exec.dynamic token checks only, an exec.dynamic WARN there is reported at INFO, and they get no Works check.
When there is neither Python nor JavaScript / TypeScript source, Works is not scored (n/a (no Python or JavaScript), null in JSON), Safe is labelled partial, Overall comes from the scored dimensions only, and the status is PARTIAL. A repo whose source is mostly in other languages is also PARTIAL with the same scores (rule in Scan status). PARTIAL means "do not read this grade as covering the whole repo"; it never fails --fail-on on its own. What the token level cannot see is in Limitations.
pip install code-guardian-mcp
The distribution is code-guardian-mcp (code-guardian on PyPI is someone else's project); the commands are code-guardian and code-guardian-mcp. To run the MCP server without installing anything: uvx code-guardian-mcp mcp.
From a clone (for the tests):
git clone https://github.com/LuminariSoftwares/code-guardian.git
cd code-guardian python -m venv .venv .venv\Scripts\activate # Windows; macOS/Linux: source .venv/bin/activate pip install -e ".[test]" python -m pytest -q
The [test] extra is pytest, build and jsonschema — the whole suite needs them, and the package's own runtime dependencies stay empty. See CONTRIBUTING.md.
code-guardian ui shows the same scan as a page in your browser, in plain words, for people who use AI to write code but do not read code well. code-guardian ui PATH checks that folder first; code-guardian ui alone opens the page and you pick a folder there. It prints one line, code-guardian ui: open http://127.0.0.1:8765/#t=…, and opens that link in your browser; the part after #t= is a key for this run, so use the printed link, not just the address. The page never changes your files, and the grade and findings are the ones code-guardian scan gives.
The gear at the top of every screen opens three choices: Theme (Dark, the default, or Light), Text size (Normal, Larger or Largest) and whether the Luminari name shows at the top. Your choices are kept by this browser only, not in a file on the computer and not by code-guardian, so another browser or a private window starts from the defaults. The page never turns light because your computer is set to light; light is only ever your choice.
Every screen fits a phone, a narrow side window (about 520 px wide) and a full or wide screen, at all three text sizes, with nothing cut off: on a phone or in a side window the summary becomes one line under the tabs that you tap to open, and the file list on the Code screen becomes a drawer. The phone is shown below; the same screen at the other sizes is result_520x900.png (side window) and result_1280x800.png (full screen).
The Code screen lists every file the check saw, not only the files with a finding, and gives each file one word. A file with a safety finding is marked High, Medium or Low by its worst one. The filter above the list picks which files you see, each with its count:
Nur der Anfang wird gezeigt; den Rest findest du im Repo