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mcp-gatehouse

by nickgeorgeseoversion 0.5.0i★ –iRuns on your computer
Registry nameio.github.nickgeorgeseo/gatehouse

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Developer tools

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

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

Run this in your terminal

claude mcp add gatehouse -- uvx mcp-gatehouse

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account nickgeorgeseo, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Developer toolsi

  • More stars than 0% of the other 4906 servers in this category
  • Published to the registry more recently than 88% of the other 4906 servers in this category
  • Basic checks equal to or better than 100% of the other 4906 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is mcp-gatehouse safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.5.0) reached the registry 5 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: GitHub, Desktop Commander, Cloudflare MCP

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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

Only the beginning is shown; read the rest in the repo

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