Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者による説明(英語の原文)
Deterministic IR/IR-LINT validation, policy packs, drift vs exports (archrad). Apache-2.0.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"deterministic": {
"command": "npx",
"args": [
"-y",
"@archrad/deterministic"
]
}
}
}ターミナルでこれを実行します
claude mcp add deterministic -- npx -y @archrad/deterministicプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"deterministic": {
"command": "npx",
"args": [
"-y",
"@archrad/deterministic"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"deterministic": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@archrad/deterministic"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月6日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント archradhq で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(0.4.1)がレジストリに届いたのは6 か月前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにNode.jsも必要です。
同じカテゴリには:Spec Driven Development, Remote Desktop Commander, Symantec Cloud DLP AIops
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
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.
Governed Symantec Cloud DLP — 14 MCP tools, read-only with audit.
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
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.冒頭だけを表示しています。続きはリポジトリで読めます