Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Deterministic IR/IR-LINT validation, policy packs, drift vs exports (archrad). Apache-2.0.
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": {
"deterministic": {
"command": "npx",
"args": [
"-y",
"@archrad/deterministic"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add deterministic -- npx -y @archrad/deterministicIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"deterministic": {
"command": "npx",
"args": [
"-y",
"@archrad/deterministic"
]
}
}
}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": {
"deterministic": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@archrad/deterministic"
]
}
}
}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 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto archradhq 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 (0.4.1) kam vor 6 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, AI Deprecations
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.
AI model shutdown dates, replacements, change feed and webhook alerts for 8 providers.
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.
Your architecture drifts before you write a single line of code. archrad validate catches it — deterministically, in CI, before the PR merges.
Define your system as a graph. ArchRAD compiles it, lints it against architecture rules, and tells you exactly what's wrong — with rule codes, not opinions.
New in 0.7.x —
archrad demoruns a full example with zero setup, andarchrad scan
drafts an IR from any repo with every node cited to
file:line. Lint findings only
decrease in this release; nothing that passed on 0.6.x can start failing.
See the changelog.
npm install -g @archrad/deterministic
archrad demo
No IR file, no flags, no config — runs from any directory. Lints a bundled example and shows you the findings:
orders-api (http) ──▶ orders-db (postgres)
⚠️ IR-LINT-DIRECT-DB-ACCESS-002: API node "orders-api" connects directly to datastore node "orders-db" Fix: Introduce a service or domain layer between HTTP handlers and persistence. ⚠️ IR-LINT-MISSING-AUTH-010: HTTP entry node "orders-api" has no auth node or auth config … ⚠️ IR-LINT-NO-HEALTHCHECK-003: No HTTP node exposes a typical health/readiness path …
archrad scan . --out draft.ir.json # draft an IR — every node cited to file:line
archrad validate --ir draft.ir.json # lint it
scan reads your Docker Compose, Kubernetes manifests, Terraform, OpenAPI, package manifests, and source code, then grades every node by confidence so you can see what was parsed versus guessed. The output is a normal IR file — review it, edit it, commit it.
Already have an OpenAPI spec or a Backstage catalog? Skip the scan:
archrad ingest openapi --spec ./openapi.yaml --out ./graph.json
archrad ingest backstage --catalog . --out ./graph.json
Once a graph is committed, archrad validate is your CI gate — exit 1 blocks the merge.
ArchRAD is a blueprint compiler and governance layer. You define your architecture as an IR — nodes, edges, allowed connections — and ArchRAD validates it against a deterministic rule engine. The same IR, the same rules, the same inputs always produce the same findings.
| Command | What it checks | Codes |
|---|---|---|
archrad validate | Graph structure + architecture lint | IR-STRUCT-* IR-LINT-* |
archrad lint | Architecture lint only (fast inner-loop; skips structural) | IR-LINT-* |
archrad explain | Canonical rule guidance without running a pass | — |
archrad policies-sha256 --dir | Generate a archrad-policy-pack.sha256 manifest for signed PolicyPacks | — |
archrad validate-drift | IR vs generated code on disk | DRIFT-* |
archrad scan | Draft IR from a repo — topology, OpenAPI, manifests, code; every node cited + graded by confidence | — |
archrad reconstruct | Draft IR from source code alone (one of scan's four signal sources, usable standalone) | — |
archrad ingest openapi | Derive IR from OpenAPI (local path or https URL for --spec; -H for URL auth headers) | — |
archrad ingest backstage | Backstage catalog-info.yaml → IR (Component, Resource, API, System; Location file targets) | — |
archrad fragment merge | Merge 2+ IR files — union by node.id (conflicts → stderr); --prefix-fragments for disjoint union | — |
archrad export | Compile IR → FastAPI or Express + Docker | — |
Ingest + merge workflows: `docs/INGEST.md`. All commands / flags: `docs/CLI_REFERENCE.md`. Codegen (`export`): `docs/EXPORT.md`.
archrad scan)archrad scan points at a repository and emits a draft IR — never a final answer, always something to review and edit. It runs six extractors, graded by how much they have to guess:
| Source | Signal | Confidence |
|---|---|---|
| Topology | docker-compose.yml, Kubernetes manifests | high — a declaration, parsed for real |
| Interface | OpenAPI / Swagger | medium — documents a real surface, but only what's documented |
| Infrastructure-as-code | Terraform (*.tf) | medium — a real declaration, but read via regex, not a true HCL parse |
| Manifest | package.json, requirements.txt, go.mod, pom.xml | low — a driver dependency implies an edge, not proof it's used |
| Code | pattern scan of source (Node.js/TS, Python, C#) | low — regex over text, no semantic understanding |
Every node and edge carries config.provenance[] — inferred_from: "file:line", a confidence, and which extractor found it — so nothing has to be taken on faith. When two extractors describe the same thing, scan merges them (keeping the highest-confidence body, unioning all provenance) instead of duplicating or erroring.
archrad scan . --dry-run # print the draft, write nothing
archrad scan ./server --out draft.ir.json # write it archrad scan . --extractors compose,manifest # only run specific extractors archrad scan . --scope all # include tests, examples, docs, and demos
CLI scans default to --scope production so fixtures, documentation examples, Storybook stories, and test-only manifests do not become production findings. Use --scope all when those artifacts are the subject of the review. Library callers retain the backwards-compatible scope: 'all' default.
The output is a normal IR file — pipe it straight into archrad validate once you've reviewed it. Full flags: `docs/CLI_REFERENCE.md`.
archrad reconstruct + --codebase)"The IR looks clean — but is that what was actually shipped?"
The validation pipeline above checks your authored IR (the design contract). The --codebase flag bridges the gap to the real codebase by reconstructing an IR from source code and comparing them.
A developer can author a compliant IR (passes all IR-STRUCT-* and IR-LINT-* rules) while the actual code bypasses the documented architecture. The most dangerous pattern: an IR that shows a clean service layer but code that directly queries the database.
# Catch discrepancies between the authored design and the shipped code
archrad validate --ir authored-ir.json --codebase ./src --report findings.html
When --codebase is provided, the pipeline runs three stages:
Implementation drift uses a separate exit threshold: `--fail-on`, `--fail-on-warning`, and `--max-warnings` apply only to IR-STRUCT-*, IR-LINT-*, and merged PolicyPack findings. IR-DRIFT-IMPL-* are gated solely by `--impl-drift-fail-on` (default: drift severities `error` fail the command).
| Code | Severity | What it catches |
|---|---|---|
IR-DRIFT-IMPL-000 | warning | Authored IR could not be parsed for drift comparison (fix structural issues first) |
IR-DRIFT-IMPL-001 | warning | IR declares HTTP-like entry nodes but reconstruction detected zero artifacts in --codebase |
IR-DRIFT-IMPL-002 | warning | HTTP / health routes in code but authored IR has no HTTP-like nodes |
IR-DRIFT-IMPL-003 | error | Direct DB connection in code, no DB edge in authored IR |
IR-DRIFT-IMPL-004 | error | HTTP route in code not present in authored IR |
IR-DRIFT-IMPL-005 | warning | Service-to-service call in code, no edge in authored IR |
IR-DRIFT-IMPL-006 | info | Auth middleware in code, no auth node in authored IR |
IR-DRIFT-IMPL-003 is the critical one. An error there means the authored IR hides a direct DB dependency.
# Just reconstruct — write the IR without comparing
archrad reconstruct --from ./src --output reconstructed-ir.json
archrad reconstruct --from ./src --language python --output py-ir.json
archrad reconstruct --from ./src --dry-run
archrad reconstruct --from ./src --verbose
| Language | Detected patterns |
|---|---|
| Node.js / TypeScript | Express, Fastify, NestJS routes + controllers; BullMQ workers, Agenda jobs, cron schedules; pg, Prisma, TypeORM, Sequelize, Mongoose, Redis, BullMQ, Firebase; Passport, express-jwt, NestJS guards, Auth0, Okta, Keycloak, Cognito; axios, got, node-fetch, gRPC; outbound HTTP URLs extracted per destination |
| Python | Flask, FastAPI, Django URLs, DRF @action; SQLAlchemy, psycopg2, asyncpg, PyMongo, motor, redis-py; login_required, jwt_required, FastAPI OAuth2; requests, httpx, aiohttp, gRPC |
| C# | Minimal API MapGet/MapPost; ASP.NET Core [HttpGet]/[ApiController]; EF Core DbContext, Npgsql, Dapper; [Authorize], AddAuthentication, JWT bearer; HttpClient, gRPC, RestSharp |
The reconstructor detects service boundaries and creates one node per service rather than collapsing everything into a single gateway:
| Layout | Detection signal | Result |
|---|---|---|
Files in routes/ or controllers/ directory | router.get/post/… in dedicated file | One service node per file |
| NestJS controllers | @Controller decorator / *.controller.ts naming | One service node per controller file |
Entry file with app.listen() | Mounts other routers | gateway node |
| BullMQ / Agenda / cron files | new Worker(…), agenda.define(…) | worker node |
| Monolithic file (all routes in one file) | Single file, no routes/ dir | Single gateway node — no forced split |
Edges between nodes reflect what the reconstruction found:
DB and cache nodes use the most user-recognizable name available:
process.env.REDIS_URL → node named "redis", process.env.SESSION_REDIS_URL → "session-redis"const userDb = new Pool(…) → node named "userDb" (for unique variable names)Node IDs and names never include env_var or other detection-method metadata.
Outbound HTTP/gRPC calls create distinct external nodes per destination:
axios.post('https://api.stripe.com/…') → node "stripe"fetch('https://auth0.com/oauth/token') → node "auth0"new PaymentServiceClient('payments-svc:50051') → node "payment" (gRPC)"external-service" nodeReconstruction is best-effort signal, not certainty:
eval, reflection, metaprogramming, and generated code are not detected.Nur der Anfang wird gezeigt; den Rest findest du im Repo