Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Flag when a tracked commitment vanishes verbatim between two versions. A signal, not a judge.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"aperture": {
"command": "uvx",
"args": [
"aperture-mcp"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add aperture -- uvx aperture-mcpIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"aperture": {
"command": "uvx",
"args": [
"aperture-mcp"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"aperture": {
"type": "stdio",
"command": "uvx",
"args": [
"aperture-mcp"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto jaysinailabs bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.2.0) kam vor 4 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Python (uv) auf deinem Computer.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, Detailing Manager
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
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.
Connect your auto detailing studio's tasks, cars, clients and revenue to Claude or ChatGPT.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
Did an agent quietly drop a commitment from your spec — and no one noticed?
English · 简体中文
AI agents now rewrite the documents that govern your work — specs, plans, ADRs, charters, AGENTS.md files. Somewhere in the edit, a constraint you set earlier can quietly disappear.
**Aperture is a *commitment tripwire*. You name the commitments you care about; it flags — word for word** — when one of them vanishes between two versions of a decision document.
Catching *"a commitment silently vanished"* is a tripwire job: it should fire on an event, deterministically, without asking permission. So Aperture ships that check on the surface that fits it best first — a git pre-commit hook / CI check that runs with no LLM, offline — and also as a CLI and an MCP server for agents to call mid-task. MCP is one adapter, not the whole product.
A signal, not a judge. It trips; *you* investigate.
Opt-in · runs locally · never trains on your data.
Aperture compares two text states of the same decision — an earlier version and a later one — and surfaces a narrow, specific kind of decision drift: when a tracked commitment’s exact text disappeared. One engine, several surfaces:
What the engine does and doesn’t do:
degraded rather than false-flag); and it can still false-flag a commitment that was merely *reformatted* (the words moved, the meaning didn’t). It does not rank options, score quality, or tell you a change was *wrong*. That judgment stays with you. Moving to the deterministic git-hook makes the check *fire reliably* — it does not widen what it can see. Same narrow, verbatim signal.If you want one sentence: Aperture is `grep` for vanished commitments, wired to fire on commit — and honest enough to admit what it can’t see.
pip install aperture-mcp # installs the `aperture` CLI + the MCP server (wire the CLI as a git hook — see below)
The PyPI package is named `aperture-mcp` because the bare name
aperturewas already taken on
PyPI. The
-mcpsuffix is a historical package-name artifact — the product is Aperture, and
MCP is only one of its surfaces. One
pip installgives you all three below.
Create a .aperture.toml — a watchlist of the commitments that must not silently vanish, per file:
fail_on_drop = true
[[watch]] path = "CHARTER.md" commitments = ["never train on your data", "data stays on the device"]
aperture check compares two git states and flags any watched commitment that disappeared verbatim:
aperture check # HEAD vs working tree (default)
aperture check --staged # HEAD vs the staged index — for a pre-commit hook aperture check --ref-a origin/main --ref-b HEAD # any two refs — for CI on a PR
Exit code 1 blocks the commit when a watched commitment dropped (the default); --warn-only prints the finding but never blocks. It’s stdlib-only, makes no network calls, and runs no model.
Wire it as a pre-commit hook — either through the pre-commit framework (uses this repo’s .pre-commit-hooks.yaml):
# .pre-commit-config.yaml
repos:
…or as a standalone .git/hooks/pre-commit:
#!/bin/sh
exec aperture check --staged
…or run it in CI as a GitHub Action on every PR (needs fetch-depth: 0 so both sides are available — see examples/github-action/aperture-check.yml):
- uses: actions/checkout@v4
with: { fetch-depth: 0 }
Kick the tires first with the bundled fixture (clone the repo): it trips on a dropped commitment
against checked-in before/after docs, no setup, fully offline —
python3 examples/git_decision_drift/git_decision_drift.py.
The same check, callable by an agent while it edits. (An MCP tool only fires if the agent *chooses* to call it — a weaker delivery for a tripwire than the git-hook, but handy mid-task.)
{
"mcpServers": { "aperture-mcp": { "command": "aperture-mcp" } } }
Prefer zero-install? Point the client at
uvxinstead:
{ "command": "uvx", "args": ["aperture-mcp"] }.
from aperture import compare, Anchor, AnchorKind
result = compare( state_a="We commit to: ci-gates-green before release; data-never-leaves-device.", state_b="We commit to: data-never-leaves-device.", anchors=[Anchor(kind=AnchorKind.COMMITMENT, id="ci-gates-green")], ) print(result.status) # DROPPED_SILENTLY print(result.anchor_violations) # the commitment that vanished
On a long task, your agent keeps rewriting the doc it works from — a plan, a spec — across sessions and edits. And every so often, a line that mattered just… vanishes.
*“Always ask before you delete anything.”* Gone. *“User data never leaves the device.”* Gone. *“The free tier stays free.”* Gone.
Nobody meant to drop them; nobody reads all 400 lines of the diff.
Aperture watches the exact lines you name. Put it on the commit — a hook that fires before the drop lands — and it won’t try to understand the doc or judge it; it just tells you which promise was there, word for word, and now isn’t. A tripwire, not a judge — and honest about the rest: soften a line, reword it, or change a number instead of deleting it, and it’ll slip past. Better you hear that now.
Aperture is a heuristic. We measured it on our own gold corpus and we publish the numbers instead of a single flattering score, because *knowing where it’s blind is the product* — recall 0.400, precision 0.667 on a 100-case corpus, labeled by an isolated LLM-judge panel (it catches 26 of 65 real drifts; ~1 flag in 3 is noise), full breakdown in docs/measured-limits.md:
| Kind of change | Does Aperture flag it? |
|---|---|
| A watched commitment deleted verbatim | ✅ Reliably — this is the one thing it’s good at (24 of 24 in the corpus) |
| A commitment reworded / softened (“must” → “should”) | ❌ Missed — the text still “matches” |
| A commitment paraphrased / restructured | ❌ Missed |
| A number / scope / negation quietly changed | ❌ Missed |
| A commitment translated to another language | ⚠️ Declines (abstains) for a *natural-language* anchor — it can’t compare verbatim across scripts, so it returns degraded rather than false-flag (a commitment dropped and translated is missed) |
The deterministic surface doesn’t widen the aperture. The git-hook fires reliably — but it still
only catches verbatim deletion. Every ❌ / ⚠️ row above is exactly as blind through the hook as
through MCP. What you gain is *when* it checks (on the commit, without anyone remembering to ask),
not *what* it can see.
Anchor style matters for that last row: the abstain applies to a natural-language anchor. A
code-identifier anchor (the
ci-gates-greenstyle the quickstart teaches) is treated as
*translation-stable* — Aperture keeps checking it across languages, so if that exact token disappears
it still flags
DROPPED_SILENTLY(usually what you want for a stable identifier).
Takeaway: treat every flag as *“look here,”* never as *“this is wrong”* — and never assume silence means nothing drifted. Aperture catches the verbatim disappearance case well and is honest that it catches little else. That narrow, reliable signal is useful precisely *because* it doesn’t pretend to be more.
Hit one of those misses on your own docs? That's the single most useful thing you can send us —
report it in ~30s (your wording is optional). Real misses guide what
we fix next.
Why not just
git diff/grep? You can reproduce the core check by hand. What Aperture adds is
that it’s wired to fire on the commit / PR event (as a hook or CI check) *and* callable
mid-task by an agent (over MCP); it returns a structured, directional result
(
ok/degraded/DROPPED_SILENTLY/ …); and it reports its own blind spots in the result
so a human can audit the gaps. It’s ergonomics + honesty around a simple, legible check — not a
smarter detector.
Long-running and multi-agent workflows drift. A constraint set in turn 3 / session 1 / by agent A gets quietly edited away forty turns later, in another session, by agent B — and nobody notices until it ships. Aperture is a preflight you can put on the documents agents maintain: name the commitments that must not silently vanish, and get a tripwire when one does — ideally on the commit itself, before the drop ever lands.
It is deliberately small and legible. It is not an AI that decides for you; it is a signal that helps *you* stay consistent with yourself.
Teams and builders who (a) let AI agents edit repo-resident decision documents — specs, plans, ADRs, charters, and AGENTS.md files — and (b) keep those documents under version control. If your agents touch text that encodes promises, Aperture gives you a cheap, honest tripwire — on the commit, in CI, or mid-task — on the ones you can’t afford to lose silently.
The repository ships a small hand-authored fixture ADR (a before/after pair under examples/git_decision_drift/fixtures/), where Aperture corre
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