Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Linters check your code. Invigil checks whether your repo is legible — to newcomers and AI agents.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"invigil": {
"command": "uvx",
"args": [
"invigil",
"mcp"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add invigil -- uvx invigil mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"invigil": {
"command": "uvx",
"args": [
"invigil",
"mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"invigil": {
"type": "stdio",
"command": "uvx",
"args": [
"invigil",
"mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 GitHub 계정 invigil 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.7.1)은 3개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Recta
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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.
Cheaper cross-chain stablecoin routes for AI agents; 5 % of the verified saving, nothing if none.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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.
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앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요