Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Linters check your code. Invigil checks whether your repo is legible — to newcomers and AI agents.
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": {
"invigil": {
"command": "uvx",
"args": [
"invigil",
"mcp"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add invigil -- uvx invigil mcpIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"invigil": {
"command": "uvx",
"args": [
"invigil",
"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": {
"invigil": {
"type": "stdio",
"command": "uvx",
"args": [
"invigil",
"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 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto invigil 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 (1.7.1) 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, AI Deprecations
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.
AI model shutdown dates, replacements, change feed and webhook alerts for 8 providers.
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.
Verify the path from installation to first successful use—for people and agents.
A package can install successfully and still fail its first useful command. Invigil combines repository-quality checks with a Cold-Start Gate that exercises declared operations and reports the evidence needed to diagnose failures.
New in development: verify an exact Python wheel before publication, outside the source checkout. The existing scorecard, published-artifact checks, and agent tools remain available. Wheel verification is unreleased; pip install invigil and the release pins below do not include it yet.
On Linux with Python 3.11+ and venv support, use the source-preview branch:
git clone --branch feat/wheel-first-use-preview https://github.com/invigil/invigil.git
cd invigil python3 -m venv .venv .venv/bin/python -m pip install -e . .venv/bin/python examples/first-use-demo/run.py
The demo runs offline and checks real wheels. Both install; one omits a required data file and fails its first-use command. Adding that file makes the same check pass. It prints the failure and saves JSON reports in a temporary directory. This is a synthetic example, not a claim about an upstream project's current release.
Demo details · Verify your own wheel · CI workflow template
The preview requires an explicit command and optional expected output. A successful run proves that operation worked in the recorded environment; it is not a general release-safety guarantee. Run unfamiliar artifacts in disposable workers without credentials—a Python venv is not a security sandbox.
*invigilate* — to watch over an exam and enforce its rules.
Invigil does not replace your existing tools; it covers the product-quality gaps they leave behind.
| Capability | Role |
|---|---|
| Repository scorecard | Checks documentation, configuration and quality conventions; suggests fixes |
| Published-artifact Cold-Start Gate | Exercises configured package/container operations and HTTP probes |
| Local-wheel first use (unreleased) | Verifies the candidate artifact; records its hash, phases and dependencies |
| Existing linters, scanners and tests | Continue checking code correctness and security alongside Invigil |
A clean-install smoke script can detect the same packaging defects. Invigil aims to make that workflow easier to configure and its reports consistent across projects.
The scorecard checks whether the project is legible to newcomers and agents. Every failing static check includes a suggested command or edit. Execution reports retain the failed step and output; they cannot infer every application's root cause.
The seven Gates cover onboarding, errors, artifact verification, supply-chain evidence, audience documentation, contribution and adoption. A grade summarizes implemented repository checks; it does not establish that an artifact was executed successfully. Use the Cold-Start Gate for execution evidence.
Published channels — pick the one that matches where you run it:
| Channel | Where it fits | One-liner |
|---|---|---|
| PyPI | local runs, Python-friendly CI | pip install invigil |
| GitHub Action | GitHub PRs | uses: invigil/invigil@v1 |
| Docker (ghcr) | GitLab, Jenkins, any non-Python CI | docker run --rm -v "$PWD:/repo" ghcr.io/invigil/invigil score /repo |
| pre-commit | offline checks on every commit | hooks invigil-layout, invigil-secrets (below) |
| MCP server | agents (Claude Code, any MCP client) | pip install "invigil[mcp]" → invigil mcp |
Every release ships all of it signed: cosign-signed wheel, sdist, and container image, plus an SPDX SBOM — verifiable with cosign verify against the GitHub OIDC identity.
These commands use the published scorecard. For wheel verification, use the source preview above.
Run it locally on any repo:
pip install invigil
invigil score . # human-readable scorecard + the exact fix for every failure invigil score . --format markdown # a PR-comment-ready table invigil score . --format json # machine-readable
Add it to CI as a report-only gate (posts a scorecard comment + badge, never blocks a PR):
# .github/workflows/quality-gate.yml
name: Quality gate on: [pull_request] permissions: { contents: read, pull-requests: write } jobs: invigil: runs-on: ubuntu-latest steps:
Flip enforce: "true" (or set project.enforce: true in .invigil.yml) when you're ready for it to block merges below the target gate.
Why the SHAs?
invigil/invigil@v1works and tracks the latest v1.x.y, but Invigil's own
actions-sha-pinnedcheck (G3) fails floating tags — including its own. Pin, and let
Dependabot bump the pins; the trailing comment is what it reads.
The action exposes the report and both badges as step outputs — pipe the scorecard into the job summary, publish the badge JSON wherever shields.io can reach it:
- uses: invigil/invigil@7f31330715bb7e42f26032ce3e921fcf78d4acea # v1.7.1
id: invigil with: { comment: "false" }
Two layers, matching the doctrine:
.env.example, a deep-health endpoint, a global error-id handler, SHA-pinned actions, an enforced lockfile, a coverage gate, a daily published-artifact smoke test, ≥5 good-first-issues, docs index, llms.txt/AGENTS.md, and more. Emits text / JSON / Markdown / a shields.io badge.invigil stranger) — on a clean runner, installs and boots configured published artifacts and probes their declared surfaces. The new local-wheel path additionally bounds setup/install/first use with one per-wheel budget and records phase results; legacy paths retain their behavior. Web services get HTTP probes; a CLI image (an artifact with a command:) is run to completion and must exit 0. One reusable workflow replaces the 60-line smoke-published.yml every repo copy-pastes:# .github/workflows/stranger-gate.yml
name: Cold-start gate on: schedule: [{ cron: "0 3 * * *" }] workflow_dispatch: jobs: stranger: uses: invigil/invigil/.github/workflows/stranger-gate.yml@7f31330715bb7e42f26032ce3e921fcf78d4acea # v1.7.1
The optional fix workflow applies mechanical fixes on a work branch and opens one batched PR. It uses invigil score --fix --pr-mode; protected-branch safeguards remain in place. Closing its PR without merging is respected until the work branch is deleted. See the CLI reference for configuration and limits.
Drop a .invigil.yml at the repo root. It's optional for the static scorecard (sensible defaults apply) and required for the Cold-Start Gate (it declares what to boot and probe). Full schema in schema/invigil.schema.json; examples in examples/.
version: 1
project: name: my-app language: python min_gate: G4 enforce: false artifacts:
probes:
boot_budget_minutes: 10
A gate developers bypass is dead weight, so Invigil is built for zero friction:
local/network/heavy. invigil check layout runs the filesystem checks with no network in ~120ms: # .pre-commit-config.yaml
Heavier, network-bound checks (scorecard, the Cold-Start Gate) stay in CI. invigil score --offline / --layer local / --group supply-chain slice it any way.
profile: strict | progressive | light, per-check weights, optional (ding without gating), thresholds.fail_on — make it *your* doctrine.→ The doctrine and the Gates covers both in full.
Legibility now has two audiences. The reader arriving cold at your repo is, more often than not, an AI agent: it has a context window instead of patience, exit codes instead of intuition, and it acts only on what the repo states machine-readably. The ai check group grades that surface — not just *presence* of llms.txt/AGENTS.md, but whether an agent can actually act on them:
| Check | The promise to the agent |
|---|---|
agents-md-actionable | Your AGENTS.md/CLAUDE.md contains runnable fenced commands, not prose |
llms-txt-shape | llms.txt is spec-shaped and fits a 10 KB context budget |
agent-context-fresh | Agent instructions aren't 90+ days staler than the source they describe |
readme-heading-hierarchy | The README chunks cleanly (one H1, real H2 sections) |
exit-codes-documented | A CLI's exit codes are enumerated — agents branch on codes, not prose |
llms-no-secrets | The machine-readable surface leaks no credentials |
agent-scope-visibility | Agent code declares its tool inventory (blast-radius precondition) |
Two artifacts fall out of it. `invigil score --format llm` — a deterministic report under ~1 KB, built to be read *by* an agent: a healthy repo costs it two lines of context. And an `ai-ready` badge, a shields.io endpoint you can put in your own README:
invigil score . --format ai-badge --output badges/ai-ready.json # commit this

In CI the Action emits it for you — steps. .outputs.ai-badge is the path to the same JSON.
##
Nur der Anfang wird gezeigt; den Rest findest du im Repo