Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Guardian layer for AI agents: identity, secrets, audit via MCP.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"haldir": {
"command": "uvx",
"args": [
"haldir"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add haldir -- uvx haldir프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"haldir": {
"command": "uvx",
"args": [
"haldir"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"haldir": {
"type": "stdio",
"command": "uvx",
"args": [
"haldir"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 ExposureGuard 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.1.0)은 7개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, EmbeddedCI BenchPod
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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.
Drive a BenchPod hardware-in-the-loop bench: power, flash, UART, I2C, CAN, analog and logic.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Scoped permissions, spend caps, an encrypted vault, and an audit log that can prove it wasn't edited — for AI agents that call tools, move money, and read secrets.
That loop is the whole idea, running live. Someone rewrites a row in the audit log — silently, straight in the database. The entry's inclusion proof no longer matches the live Merkle root, and the verdict flips. Not caught by monitoring, not caught by a diff: caught by arithmetic, because the root is a hash of what the log actually contains and the earlier Signed Tree Head is already pinned somewhere you don't control.
→ Try it yourself. Run haldir serve (below) and open http://127.0.0.1:8000/demo — the same tamper demo, against an instance on your own machine. It ships inside the package, so there is nothing to download and no account involved.
pip install haldir
haldir serve
That starts a real Haldir on this machine — SQLite, no Docker, no Postgres, no account. It generates an encryption key, applies the schema, mints an API key, and points the CLI at itself, so the next command just works:
$ haldir serve
Haldir is running http://127.0.0.1:8000 data: ~/.haldir
Your API key (saved to the Haldir CLI config): hld_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
Try it: haldir overview haldir session create --agent my-agent --scopes read
From there, point anything at it — the CLI, the Python SDK, an MCP client — or read the API reference at /docs on the instance you started. When you want Postgres and containers, haldir init && haldir dev scaffolds and runs that instead; SELF_HOSTING.md covers the rest.
Works with Claude Code, Cursor, LangChain, CrewAI, AutoGen, LlamaIndex and the Vercel AI SDK — anything that can make an HTTP call or speak MCP. MIT licensed: self-host it, or point at haldir.xyz (free tier, no signup).
Here's what Haldir actually looks like — no diagrams, no spec sheets, just screenshots of the real thing.
Without Haldir, an agent calls whatever API it wants, spends whatever it wants, and accesses whatever secret it finds — with zero oversight and zero audit trail. With Haldir, every action is scoped, spend-limited, logged immutably, and secrets never leave the vault.
Here's the three things you'd see as a new visitor, in order:
Here's the dashboard with the important parts labeled:
The sidebar on the left takes you anywhere. The numbered markers point at the parts you'll actually use: your tenant and tier, the live counts, and your API keys by prefix — with the revoke button right there, so ending an agent's access never means opening a database shell.
All of these ship inside the package and are served by haldir serve, so they work on your machine with no account and nothing to deploy:
→ The tamper demo at /demo/tamper — the one in the GIF above. Rewrite a real log row and watch the inclusion proof stop matching the Merkle root. Nothing is simulated; it is the same Merkle code the API ships.
→ The playground at /demo — four steps walk the happy path (mint a key, open a scoped session, check a permission, write to the audit trail), then three try to break it: spend past the cap, revoke the session mid-flight, and act after revocation. Pick a scope that was never granted in step 03 to see a denial as well as an approval.
→ The gallery at /gallery — every screenshot on this page in one place, if you'd rather look than read.
Want something to run without installing anything? There is a one-file demo binary — no Python, no clone — and a three-probe fixture that ships with the package. Both are in [DEMO.md](DEMO.md): what to run, what you'll see, and what each probe is built to catch.
The full reference is at /docs and /openapi.json on whichever instance you are running. Below: the Python quickstart, performance numbers, and compliance mapping.
There is a hosted option at [haldir.xyz](https://haldir.xyz) — free tier, no signup. haldir serve is the path that works today, and the one to reach for if the cloud is not what you want anyway.
Same product either way.
| Self-host | Cloud (haldir.xyz) | |
|---|---|---|
| Price | Free forever | Free tier + paid plans |
| You run | API + Postgres | Nothing |
| Best for | Regulated, air-gapped, "must own data" | "Just make it work" |
The cloud tier is free to start and needs no signup. We're taking 5 design partners — 30 days, full access, direct line to the founder: sterling@haldir.xyz.
git clone https://github.com/ExposureGuard/haldir.git
cd haldir cp .env.example .env python3 -c 'import base64, os; print(base64.urlsafe_b64encode(os.urandom(32)).decode())'
docker compose up -d curl http://localhost:8000/healthz
Full self-hosting guide: SELF_HOSTING.md
pip install haldir
That's it — point at https://haldir.xyz, no signup for the free tier.
Install once, drive the whole platform from the terminal:
$ haldir overview
Haldir tenant overview acct_xyz123 · tier free · 2026-09-30T18:42:11+00:00
Status ● ok API calls 4,217 / 10,000 ████████░░░░░░░░░░░░ 42.2% Spend $ 47.30 this month Sessions 3 active · 1/1 agents Vault 8 secrets · 62 accesses this month Audit 1,847 entries · 0 flagged (7d) · chain ✓ Webhooks 2 registered · 541 deliveries (24h) · 99.82% success Approvals 1 pending
pip install haldir
haldir login # one-time; stashes API key haldir overview --watch # top-style live dashboard haldir status # green/yellow/red component pills haldir ready # exits 0/1, perfect for CI haldir audit trail --agent my-bot # the last N entries haldir audit export --format=jsonl --out audit-2026-04.jsonl haldir audit verify # hash chain integrity check haldir webhooks deliveries # last 20 retry attempts haldir migrate up # apply pending schema migrations
haldir --help lists every command and [CLI.md](CLI.md) is the full reference — what each one does, the flags it takes, and which commands support --json (not all of them do; the reference says which).
AI agents are calling APIs, spending money, and accessing credentials with zero oversight. Haldir is the missing layer:
| Without Haldir | With Haldir |
|---|---|
| Agent has unlimited access | Scoped sessions with permissions |
| Secrets in plaintext env vars | AES-256-GCM encrypted vault |
| No spend limits | Per-session budget enforcement |
| No record of what happened | Immutable, tamper-evident audit |
| No human oversight | Approval workflows with webhooks |
| Agent talks to tools directly | Proxy intercepts + enforces |
Everything on the right is one process in front of your tools. Your agent keeps its existing tool calls; Haldir answers first:
from haldir import HaldirClient
haldir serve printed above.h = HaldirClient(api_key="hld_xxx", base_url="http://127.0.0.1:8000")
session = h.create_session("my-agent", scopes=["read", "spend:50"])
h.store_secret("stripe_key", "sk_live_xxx")
key = h.get_secret("stripe_key", session_id=session["session_id"])
h.authorize_payment(session["session_id"], 29.99)
h.log_action(session["session_id"], tool="stripe", action="charge", cost_usd=29.99)
h.revoke_session(session["session_id"])
Under the hood that's four HTTP calls — mint a key, open a session, check a permission, write to the audit chain:
Scoped sessions with permissions, spend limits, and TTL. No session = no access.
curl -X POST https://haldir.xyz/v1/sessions \
-H "Authorization: Bearer hld_xxx" \ -H "Content-Type: application/json"
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요