Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Linters check your code. Invigil checks whether your repo is legible — to newcomers and AI agents.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
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 mcpPaste 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.
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.
Runs on your computer; the tool list appears in your AI app after you install it.
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
The registry name was verified with the GitHub account invigil, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
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.
The registry does not list a required key, though some servers ask you to sign in on first use.
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).
The GitHub repo last changed –, and the latest version (1.7.1) reached the registry 3 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, FOGA node
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
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
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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.
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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