原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Invigil

作者:invigil版本 1.7.1i★ –i在你的电脑上运行
注册名称io.github.invigil/invigil

安装

概览

作者提供的说明(英文原文)

Linters check your code. Invigil checks whether your repo is legible — to newcomers and AI agents.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 其他

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "invigil": {
      "command": "uvx",
      "args": [
        "invigil",
        "mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add invigil -- uvx invigil mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "invigil": {
      "command": "uvx",
      "args": [
        "invigil",
        "mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "invigil": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "invigil",
        "mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 invigil 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32410 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32410 个服务器的 20% 更新
  • 基础检查结果等于或优于此分类中其他 32410 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Invigil 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(1.7.1)于3个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, debuff

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211昨天更新
安装

debuff

作者:debuffjp

Let coding agents play, test and tune your 2D web game: live state, explained errors, replays, fuzz.

在你的电脑上运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Invigil

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.

Try the first-use demo (source preview)

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.


How Invigil fits in your stack

Invigil does not replace your existing tools; it covers the product-quality gaps they leave behind.

CapabilityRole
Repository scorecardChecks documentation, configuration and quality conventions; suggests fixes
Published-artifact Cold-Start GateExercises 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 testsContinue 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.


Why

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.

Install

Published channels — pick the one that matches where you run it:

ChannelWhere it fitsOne-liner
PyPIlocal runs, Python-friendly CIpip install invigil
GitHub ActionGitHub PRsuses: invigil/invigil@v1
Docker (ghcr)GitLab, Jenkins, any non-Python CIdocker run --rm -v "$PWD:/repo" ghcr.io/invigil/invigil score /repo
pre-commitoffline checks on every commithooks invigil-layout, invigil-secrets (below)
MCP serveragents (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.

Quick Start

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:

  • uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
  • uses: invigil/invigil@7f31330715bb7e42f26032ce3e921fcf78d4acea # v1.7.1 with: enforce: "false" # flip to true once the grade is stable

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@v1 works and tracks the latest v1.x.y, but Invigil's own

actions-sha-pinned check (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" }

  • run: cat "${{ steps.invigil.outputs.report }}" >> "$GITHUB_STEP_SUMMARY"

outputs.badge → grade badge JSON · outputs.ai-badge → ai-ready badge JSON

How it works

Two layers, matching the doctrine:

  • Static Doctrine Scorecard (every PR, seconds) — inspects the repo filesystem and GitHub metadata: LICENSE, README length, .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.
  • Cold-Start Gate (nightly, reusable — 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

Fix by PR

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.

Configuration

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:

  • type: pypi name: "my-app[all]"
  • type: ghcr image: ghcr.io/me/my-app:latest port: 8000

probes:

  • { url: "/", expect_status: 200 }
  • { url: "/api/things", expect_json_count: { min: 5 } }

boot_budget_minutes: 10

Lightweight & modular

A gate developers bypass is dead weight, so Invigil is built for zero friction:

  • Fast offline groups for pre-commit — each check is tagged local/network/heavy. invigil check layout runs the filesystem checks with no network in ~120ms:
  # .pre-commit-config.yaml
  • repo: https://github.com/invigil/invigil rev: v1 # tracks the latest v1.x.y hooks: [{ id: invigil-layout }, { id: invigil-secrets }]

Heavier, network-bound checks (scorecard, the Cold-Start Gate) stay in CI. invigil score --offline / --layer local / --group supply-chain slice it any way.

  • It bends instead of forking. profile: strict | progressive | light, per-check weights, optional (ding without gating), thresholds.fail_on — make it *your* doctrine.
  • Resilient by design. A scorecard.dev timeout is a SKIP excluded from the grade — never a false A-to-C downgrade, never a crashed build.

→ The doctrine and the Gates covers both in full.

When your user is an agent

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:

CheckThe promise to the agent
agents-md-actionableYour AGENTS.md/CLAUDE.md contains runnable fenced commands, not prose
llms-txt-shapellms.txt is spec-shaped and fits a 10 KB context budget
agent-context-freshAgent instructions aren't 90+ days staler than the source they describe
readme-heading-hierarchyThe README chunks cleanly (one H1, real H2 sections)
exit-codes-documentedA CLI's exit codes are enumerated — agents branch on codes, not prose
llms-no-secretsThe machine-readable surface leaks no credentials
agent-scope-visibilityAgent 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
![AI-ready](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/OWNER/REPO/main/badges/ai-ready.json)

In CI the Action emits it for you — steps. .outputs.ai-badge is the path to the same JSON.

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