Prototype · Preview: every server in the official registry, synced every 30 minutes. Reviews and accounts come in a later step.
PopNx MCPMCP servers for people who use AI · explained in plain words

Invigil

by invigilversion 1.7.1i★ –iRuns on your computer
Registry nameio.github.invigil/invigil

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

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

Run this in your terminal

claude mcp add invigil -- uvx invigil mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account invigil, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32417 servers in this category
  • Published to the registry more recently than 20% of the other 32417 servers in this category
  • Basic checks equal to or better than 100% of the other 32417 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Invigil safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.7.1) reached the registry 3 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, FOGA node

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Spec Driven Development

by formulahendry

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

Runs on your computer★ 440MITUpdated 14 months ago
Install

Remote Desktop Commander

by desktop-commander

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

Runs in the cloud★ 211Updated yesterday
Install

FOGA node

by garyyang-finchip

A Finch OG Agent cell as an MCP server: read the world, dry-run and take ERC-8414 tenders by policy.

Computer or cloudUpdated today
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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.

##

Only the beginning is shown; read the rest in the repo

Ask PopNx