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mcp-gatehouse

作者:nickgeorgeseo版本 0.5.0i★ –i在你的电脑上运行
注册名称io.github.nickgeorgeseo/gatehouse

安装

概览

作者提供的说明(英文原文)

Permission tiers, approval gates, and audit logging for MCP servers - the server is the gatekeeper

PopNx MCP 的三大支柱

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。

它能帮你做什么

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。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 开发者工具

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

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": {
    "gatehouse": {
      "command": "uvx",
      "args": [
        "mcp-gatehouse"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add gatehouse -- uvx mcp-gatehouse

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "gatehouse": {
      "command": "uvx",
      "args": [
        "mcp-gatehouse"
      ]
    }
  }
}

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。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "gatehouse": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "mcp-gatehouse"
      ]
    }
  }
}

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。

它能做什么

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。

基础检查i

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8日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 nickgeorgeseo 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    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“开发者工具”中的其他服务器比较i

  • 星标数多于此分类中其他 4910 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 4910 个服务器的 88% 更新
  • 基础检查结果等于或优于此分类中其他 4910 个服务器的 100%

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。

常见问题

mcp-gatehouse 安全吗?

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。

它需要哪些密钥或代码?

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。

它在我的电脑上运行还是在云端?

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)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.5.0)于5天前进入注册中心。

哪些应用可以使用它?

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)。

有什么可以替代它?

同一分类中有:GitHub, Desktop Commander, Cloudflare MCP

替代选择

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

GitHub

作者:github

Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.

电脑或云端★ 34,245MIT4天前更新
安装

Desktop Commander

作者:wonderwhy-er

MCP server for terminal commands, file operations, and process management

在你的电脑上运行★ 10,225MIT16天前更新
安装

Cloudflare MCP

作者:cloudflare

Cloudflare MCP servers

在云端运行★ 4,446Apache-2.014个月前更新
安装

作者的 README

打开 README

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。

mcp-gatehouse

Project page & docs: nickgeorgeai.com/open-source/mcp-gatehouse · PyPI

Permission tiers, approval gates, and audit logging for MCP servers. The server is the gatekeeper: you decide what an AI can read, what it can write, and what's off-limits — and every action gets logged.

Most MCP servers hand the model every tool at full strength and keep no record of what it did. That's fine for a demo. It's not fine the day an agent has write access to your CRM, your books, or your order system. mcp-gatehouse is the missing gate, enforced inside the server — no proxy, no external policy service, no dependencies beyond the official mcp SDK.

pip install mcp-gatehouse

The demo server in Claude Code: the model asks to cancel an order, the gate asks *you* in Claude Code's own UI, and the audit log records the call as asked, then done.

The 1:21 demo runs the package's demo server in a terminal: the install, the one-decorator change, a cancel refused and one approved, and the audit log they left. No sound.

What you get

Permission tiersEvery tool is declared READ, WRITE, or DESTRUCTIVE — and the tier also emits honest spec ToolAnnotations (readOnlyHint / destructiveHint), which the wrapper won't let you override to lie.
Approval gatesTiers you choose require a sign-off before the tool runs, asked right in the MCP client (Claude Code, Cursor, VS Code) or by any callable you write: a terminal prompt, a Slack ping, a ticket. Fails closed: a gated tool with no approver configured is denied, not waved through.
Audit logAppend-only JSONL, one line per call — allowed, denied, failed, or cancelled — with UTC timestamps and durations. The answer to "what did the AI actually do?" six months later.
RedactionArgument keys you name (api_key, password, token, client_secret, … by default) are masked before they reach the log *or* the approver — however they're spelled: apiKey, API-Key and api_key are the same key.
DenylistBlock a tool outright, whatever its tier.

Quickstart

from mcp.server.mcpserver import MCPServer

from mcp_gatehouse import ( AccessTier, AuditLog, ElicitationApprover, Gatehouse, Policy, terminal_approver, )

mcp = MCPServer("order-desk") gatehouse = Gatehouse( mcp,

Ask in the client's own UI; prompt on the terminal if it can't show a form.

policy=Policy(approver=ElicitationApprover(fallback=terminal_approver)), audit=AuditLog(path="~/order-desk/audit.jsonl"), )

@gatehouse.tool(tier=AccessTier.READ) def lookup_order(order_id: str) -> str: """Look up an order's status.""" ...

@gatehouse.tool(tier=AccessTier.DESTRUCTIVE) def cancel_order(order_id: str) -> str: """Cancel an order. Runs only if the approver says yes.""" ...

mcp.run()

That's the whole integration: build your MCPServer exactly as the SDK docs show, but register tools through the gatehouse. Schema generation (including Annotated[..., Field(description=...)] parameter docs), transports, and everything else work unchanged — the guard preserves the function's signature. Sync tools still run in a worker thread, exactly as they would on a bare MCPServer.

Approve in the client

ElicitationApprover puts the question in front of the person using the MCP client, as a form with one box to tick, showing the tool, its tier and its arguments (secrets already masked). MCP calls this elicitation. Claude Code, Cursor and VS Code support it. The model can't answer the form, and you run nothing beside the server.

It works under both protocol revisions in use:

  • Up to 2025-11-25 the form goes to the client mid-call and the gate waits for it, under approval_timeout like any approver.
  • From 2026-07-28 there's no channel for that. The call hands the question back to the client and runs when the client calls again with the answer. The SDK seals that round's state and binds it to the tool and its exact arguments. The gate also checks that the answer is to the question it asked, that it arrived within approval_timeout (an hour if none is set), and that each approval runs its call only once.

Anything but a ticked box (decline, cancel, closing the form, an unticked box, a malformed answer) is a refusal. When the client can't be asked, the fallback decides; with no fallback, the call is denied. A tool that runs its own multi-round input flow, through Resolve(...) parameters or by returning InputRequiredResult, gets the fallback too, since one call has one such channel. Single-use is tracked per process.

Elicitation trusts the client to show the form to a person. A client or hook set to accept forms on its own can approve too. When the approval must come from outside the client, use an out-of-band approver instead.

Other approvers

terminal_approver asks on the controlling terminal (/dev/tty), never stdin — over stdio, stdin *is* the protocol pipe, so a plain input() approver would corrupt it. An approver is any callable, sync or async, that takes an ApprovalRequest and returns True to allow; sync ones run in a worker thread from a pool of their own, so a human taking their time doesn't stall other calls, and a pile of pending approvals can't take the threads your sync tools need. If the approver raises (Slack down, ticket API timing out), the call is denied and the failure is logged.

Give approvals a deadline so a sign-off nobody gives doesn't hang the call:

Policy(approver=terminal_approver, approval_timeout=120)

Past it, the call is denied and logged as approval timed out. Approvers see the deadline as request.deadline (a time.monotonic() value), and terminal_approver withdraws its prompt when it passes. A sync approver that ignores it finishes in the background and its answer is dropped. With no timeout set, the gate waits as long as the approver takes.

Under the default policy, DESTRUCTIVE requires approval and everything is audited. Gate writes too with one line:

Policy(require_approval=frozenset({AccessTier.WRITE, AccessTier.DESTRUCTIVE}), ...)

Add your own secret-bearing keys without losing the defaults:

from mcp_gatehouse import DEFAULT_REDACT

Policy(redact=DEFAULT_REDACT | {"card_pin"}, ...)

What the audit trail looks like:

{"ts": "2026-07-16T14:02:11+00:00", "tool": "lookup_order", "tier": "read", "outcome": "ok", "arguments": {"order_id": "4417"}, "duration_ms": 0.42}

{"ts": "2026-07-16T14:02:38+00:00", "tool": "add_note", "tier": "write", "outcome": "ok", "arguments": {"order_id": "4417", "note": "call back", "api_key": "«redacted»"}, "duration_ms": 1.08} {"ts": "2026-07-16T14:03:05+00:00", "tool": "cancel_order", "tier": "destructive", "outcome": "denied", "reason": "approver refused", "arguments": {"order_id": "4417"}} {"ts": "2026-07-16T14:05:40+00:00", "tool": "cancel_order", "tier": "destructive", "outcome": "cancelled", "reason": "awaiting approval", "arguments": {"order_id": "4418"}}

outcome is ok, denied (reason says why), error (the tool raised; reason is the exception type), pending, or cancelled. pending is a call whose approval was asked in the client over the 2026-07-28 round trip: the verdict follows on a line of its own when the client comes back, so a pending line with nothing after it is a question nobody answered. cancelled means the client gave up, or the server shut down, before the call finished. reason says when. awaiting approval means the tool never ran. tool running comes with duration_ms, and the tool may have done part of its work. A sync tool can't be stopped partway: its worker thread runs to the end, and the line says ok or error as usual. The gate only writes the line; the cancellation goes on as it would without it.

Try the demo

The package ships a runnable order-desk server with all three tiers wired up. Approvals are asked in the client when it can show a form, with a terminal prompt as the fallback. Add it to any MCP client that speaks stdio. For Claude Code:

claude mcp add gatehouse-demo -- uvx mcp-gatehouse --audit-log /tmp/gatehouse-audit.jsonl

For Claude Desktop, in claude_desktop_config.json:

{

"mcpServers": { "gatehouse-demo": { "command": "uvx", "args": ["mcp-gatehouse", "--audit-log", "/tmp/gatehouse-audit.jsonl"] } } }

Or run mcp-gatehouse-demo yourself after pip install mcp-gatehouse. Ask the model to list the orders and cancel one, then watch the verdict land in the audit log either way. The audit log goes to --audit-log, else $MCP_GATEHOUSE_AUDIT_LOG, else ./audit.jsonl — falling back to ~/.mcp-gatehouse/audit.jsonl when the working directory isn't writable (desktop clients often launch servers from /). The server prints the path it chose to stderr.

In a client that supports elicitation (Claude Code, Cursor, VS Code), cancel_order brings up an approval form in the client: tick the box to let it run. An approval nobody gives is denied after two minutes.

Other clients get the terminal fallback, which needs the server to have a terminal it can ask on. Whether it gets one depends on how the client starts it:

  • TypeScript SDK clients (the StdioClientTransport in 1.x and 2.x) keep the server in the client's terminal session. Start such a client from an ordinary terminal, one not running a full-screen program, and the prompt appears there. An unanswered prompt is denied after two minutes.
  • Python SDK clients (stdio_client in 1.x and 2.x), and anything built on them, start every server in a session of its own. The server has no controlling terminal even when you run the client from one, so it can't prompt: cancel_order is denied, and stderr says why.
  • Desktop apps that launch servers in the background give them no terminal, and full-screen terminal UIs are using theirs. Denied too.

Every denial is the gate failing closed, as designed. Where the prompt can't reach you, approve out-of-band instead: an approver is any callable, so it can post to Slack, open a ticket or wait on a queue. examples/orders_server.py is the same server as a copyable template.

Design notes

  • Enforcement lives inside the server, at the tool boundary. A proxy can't see your tools' semantics, and a policy service is one more thing to deploy. A 40-person plant doesn't have a platform team; this is a

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