ipdata MCP by usefulapi
Look up location, network, company and threat data for IP addresses and ASNs in ipdata.
作者提供的说明(英文原文)
Guardian layer for AI agents: identity, secrets, audit via MCP.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"haldir": {
"command": "uvx",
"args": [
"haldir"
]
}
}
}在终端中运行这条命令
claude mcp add haldir -- uvx haldir粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"haldir": {
"command": "uvx",
"args": [
"haldir"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"haldir": {
"type": "stdio",
"command": "uvx",
"args": [
"haldir"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 ExposureGuard 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.1.0)于7个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
同一分类中有:ipdata MCP by usefulapi, MaxMind minFraud MCP by usefulapi, Lambda Labs MCP by usefulapi
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Look up location, network, company and threat data for IP addresses and ASNs in ipdata.
MCP server for MaxMind minFraud — score transactions for fraud risk from your AI assistant.
Read GPU instances, types, images, filesystems and firewall rules; launch and terminate instances.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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"
只显示了开头部分;其余内容请在仓库中阅读