Verifies repository legibility and package functionality for both human developers and AI agents through static scorecards and cold-start gates.
Also known as invigil/invigil
- Stars
- 1
- Tools
- —
- Downloads, 30 days
- 191
- Latest version
- 1.7.1
- Last commit
- Nov 13, 2026
- License
- Apache-2.0
What is Invigil MCP?
Invigil verifies repository legibility and package functionality for both human developers and AI agents through static scorecards and cold-start gates.
Summary generated from the project's README
About Invigil MCP server
Invigil provides a dual-layer verification system designed to ensure software repositories are legible for both human developers and AI agents. It functions through a Static Doctrine Scorecard that inspects filesystem metadata, documentation quality, and configuration standards, alongside a Cold-Start Gate that executes installed packages to confirm they actually work in a clean environment. This tool helps maintain high product quality by catching packaging defects that standard linters or security scanners might miss.
Developers can run Invigil locally via PyPI, integrate it into GitHub Actions, or deploy it using Docker for non-Python environments. For those using AI-driven development workflows, it can be installed as an MCP server using the invigil[mcp] extra. The system supports various output formats including JSON, Markdown, and specialized machine-readable reports for LLMs. While the scorecard provides a grade based on repository standards, the Cold-Start Gate uses configured probes and HTTP checks to provide execution evidence.
What you can do with it
- 1Verify repository legibility for AI agentsAn AI client can use the scorecard to check if a repository contains actionable instructions and properly formatted documentation like llms.txt.
- 2Validate package functionality after installationA developer can use the Cold-Start Gate to ensure a package's declared operations work correctly on a clean runner.
- 3Automate quality gates in CI/CDYou can configure a GitHub Action to post a scorecard as a comment on pull requests to maintain project standards.
- 4Check local filesystem and secretsDevelopers can run fast offline checks to ensure the repository layout and secret management follow project rules.
Written from the project's README. Every use case is checked against a quote from it.
How to install Invigil MCP
Formats verified 10 Nov 2026Add to CursorAdd to GooseInstall Invigil MCP in Claude Code
$ claude mcp add invigil -- uvx invigilInstall Invigil MCP in Cursor
~/.cursor/mcp.json
{
"mcpServers": {
"invigil": {
"command": "uvx",
"args": [
"invigil"
]
}
}
}Install Invigil MCP in VS Code
.vscode/mcp.json
{
"servers": {
"invigil": {
"type": "stdio",
"command": "uvx",
"args": [
"invigil"
]
}
}
}Install Invigil MCP in VS Code CLI
$ code --add-mcp '{"name":"invigil","type":"stdio","command":"uvx","args":["invigil"]}'Install Invigil MCP in Claude Desktop
claude_desktop_config.json
{
"mcpServers": {
"invigil": {
"command": "uvx",
"args": [
"invigil"
]
}
}
}Install Invigil MCP in Codex
$ codex mcp add invigil -- uvx invigilInstall Invigil MCP in Codex config.toml
~/.codex/config.toml
[mcp_servers.invigil] command = "uvx" args = ["invigil"]
Install Invigil MCP in Gemini CLI
$ gemini mcp add -s user invigil uvx -- invigilInstall Invigil MCP in Gemini settings.json
~/.gemini/settings.json
{
"mcpServers": {
"invigil": {
"command": "uvx",
"args": [
"invigil"
]
}
}
}Automated checks
Ran Nov 14, 2026Full report →Passed our automated checks. That is not a security audit: read the code and give the server the narrowest access it needs. How checks work
- Source repository linked and reachableinvigil/invigil is public and reachablegithub.com/invigil/invigil ↗Pass
- Package names this repository as its sourceinvigil names invigil/invigil as sourcepypi.org/project/invigil/ ↗Pass
- Build provenance (Sigstore attestation)Sigstore attestation for invigilpypi.org/project/invigil/ ↗Pass
- Open source license (OSI)Apache-2.0spdx.org/licenses/Apache-2.0.html ↗Pass
- Commit or release in the last yearLast commit or release 2026-11-13github.com/invigil/invigil ↗Pass
- OpenSSF ScorecardOpenSSF Scorecard 7.9 / 10; weakest: Code-Review 0, CII-Best-Practices 0, Fuzzing 0scorecard.dev/viewer/?uri=github.com/invigil/invigil ↗Pass
- Package name not close to a popular packageNo popular package one edit away from invigilPass
- No critical advisory in the package or its dependencies2 resolved dependencies checked; no critical advisoryosv.dev ↗Pass
- No hidden instructions to the model0 tool descriptions and the README read; no override phrases, credential paths or hidden charactersPass
- Destructive tools are labelledNot checked
- Remote endpoint answers the MCP handshakeNot checked
README
View on GitHubInvigil
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.
| 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.
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:
| 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 "$PWD:/repo" ghcr.io/invigil/invigil score /repo |
| pre-commit | offline checks on every commit | hooks invigil-layout, invigil-secrets (below) |
| MCP server | agents (Claude Code, any MCP client) | pip install "invigil[mcp]" → invigil mcp |
Every release ships all of it signed: cosign-signed wheel, sdist, and container image, plus an
SPDX SBOM — verifiable with cosign verify against the GitHub OIDC identity.
Quick Start
These commands use the published scorecard. For wheel verification, use the source preview above.
Run it locally on any repo:
pip install invigil
invigil score . # human-readable scorecard + the exact fix for every failure
invigil score . --format markdown # a PR-comment-ready table
invigil score . --format json # machine-readable
Add it to CI as a report-only gate (posts a scorecard comment + badge, never blocks a PR):
# .github/workflows/quality-gate.yml
name: Quality gate
on: [pull_request]
permissions: { contents: read, pull-requests: write }
jobs:
invigil:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
- uses: invigil/invigil@7f31330715bb7e42f26032ce3e921fcf78d4acea # v1.7.1
with:
enforce: "false" # flip to true once the grade is stable
Flip enforce: "true" (or set project.enforce: true in .invigil.yml) when you're ready for
it to block merges below the target gate.
Why the SHAs?
invigil/invigil@v1works and tracks the latest v1.x.y, but Invigil's ownactions-sha-pinnedcheck (G3) fails floating tags — including its own. Pin, and let Dependabot bump the pins; the trailing comment is what it reads.
The action exposes the report and both badges as step outputs — pipe the scorecard into the job summary, publish the badge JSON wherever shields.io can reach it:
- uses: invigil/invigil@7f31330715bb7e42f26032ce3e921fcf78d4acea # v1.7.1
id: invigil
with: { comment: "false" }
- run: cat "${{ 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 acommand:) is run to completion and must exit 0. One reusable workflow replaces the 60-linesmoke-published.ymlevery 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 layoutruns 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-chainslice it any way. -
It bends instead of forking.
profile: strict | progressive | light, per-checkweights,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:
| 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.<id>.outputs.ai-badge is the path to the same JSON.
MCP server
Agents don't have to shell out — Invigil speaks MCP natively (mcp-name: io.github.invigil/invigil):
pip install "invigil[mcp]" # optional extra; the core CLI stays zero-dep
invigil mcp # stdio server
// e.g. .mcp.json for Claude Code — any MCP client works
{ "mcpServers": { "invigil": { "command": "uvx", "args": ["--from", "invigil[mcp]", "invigil", "mcp"] } } }
Three read-only tools: evaluate_repo (the scorecard, llm or json format),
check_group (one fast offline group), and preview_fixes (the mutation plan --fix
would apply — the agent applies changes with its own edit tools, so nothing here writes).
The doctrine
Absence of complaints is not absence of problems — silence is the loudest negative signal a project gets. That's the Silent User Doctrine, and Invigil is its enforcement: what the Gates mean and how to tune them.
Stability
Invigil is Alpha, and docs/stability.md says exactly what that
buys you: the CLI, exit codes, JSON shape, badge JSON and MCP tools are stable enough to
automate against; individual check verdicts are not, and every report carries a
doctrine_version so you can tell your repo regressed from the ruler moved.
Contributing
Issues and PRs welcome — see CONTRIBUTING.md and good first issues. Invigil grades itself in CI; self-score is currently report-only. See the scoped beginner tasks and benchmark tasks.
License
Apache-2.0 — see LICENSE.
Invigil MCP questions
How do I add Invigil MCP to Claude Code?
Run claude mcp add invigil -- uvx invigil in your terminal. Add --scope user to make it available in every project.
How do I add Invigil MCP to Cursor?
Open ~/.cursor/mcp.json and add the server under mcpServers, using the Cursor config shown in the install section above.
What does Invigil check?
It checks repository legibility for humans and agents, combining repository-quality checks with a Cold-Start Gate that exercises declared operations.
How can I use Invigil with an AI agent?
You can install it as an MCP server using pip install "invigil[mcp]" and run it with invigil mcp to allow agents like Claude Code to interact with it.
Can Invigil help make a repository AI-ready?
Yes, it includes an 'ai' check group that evaluates if machine-readable surfaces like llms.txt or AGENTS.md are actionable and correctly shaped for agents.
Is Invigil a security sandbox?
No, running unfamiliar artifacts in a Python venv is not a security sandbox; you should use disposable workers without credentials.