Prototipo · Versión preliminar: todos los servidores del registro oficial, sincronizados cada 30 minutos. Las reseñas y las cuentas llegarán en una etapa posterior.
PopNx MCPServidores MCP para quienes usan IA · explicados con palabras sencillas

mcp-gatehouse

de nickgeorgeseoversión 0.5.0i★ –iSe ejecuta en tu computadora
Nombre en el registroio.github.nickgeorgeseo/gatehouse

Instalar

Resumen

Descripción del creador (original en inglés)

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

Los tres pilares de PopNx MCP

Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.

Qué puedes hacer con él

Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.

  • Conexión: Se ejecuta en tu computadora
  • Transporte: stdio
  • Categoría: Otros

Instalación

Elige la app de IA que usas y copia la configuración.

Antes de instalar

Necesitas

  • PyPIuv de Python instalado (para el comando uvx)

¿Qué app usas?

Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.

Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json

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

Ejecuta esto en tu terminal

claude mcp add gatehouse -- uvx mcp-gatehouse

Abrir en Cursor

O copia la configuración tú

Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json

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

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Abrir en VS Code

O copia la configuración tú

Pégalo en .vscode/mcp.json de tu proyecto

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

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.

Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.

Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.

Qué puede hacer

Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.

Revisiones básicasi

Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026

  • ✓ Superada

    El creador coincide con el repo

    El nombre en el registro se verificó con la cuenta de GitHub nickgeorgeseo, dueña del repo

  • … Aún sin revisar

    Sigue en mantenimiento

    Todavía no hemos leído este repo en GitHub

  • … Aún sin revisar

    Tiene licencia

    Todavía no hemos leído este repo en GitHub

  • – No aplica

    El endpoint responde

    Este se ejecuta en tu computadora; no hay endpoint en internet

  • – No aplica

    Inicio de sesión con OAuth

    Se ejecuta en tu computadora y usa ajustes locales en su lugar

  • … Aún sin revisar

    Sin instrucciones ocultas en las descripciones de herramientas

    Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet

Comparado con otros en Otrosi

  • Más estrellas que el 0% de los otros 32718 servidores de esta categoría
  • Publicado en el registro más recientemente que el 89% de los otros 32718 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 32718 servidores de esta categoría

Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.

Preguntas frecuentes

¿Es seguro mcp-gatehouse?

Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.

¿Qué claves o códigos necesita?

El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.

¿Se ejecuta en mi computadora o en la nube?

Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).

¿Sigue en mantenimiento?

El repo de GitHub cambió por última vez –, y la última versión (0.5.0) llegó al registro hace 4 días.

¿Qué apps pueden usarlo?

Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.

¿Qué puedo usar en su lugar?

En la misma categoría: Spec Driven Development, Remote Desktop Commander, MemberVault MCP by usefulapi

Alternativas

Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.

Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi

Spec Driven Development

de formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Se ejecuta en tu computadora★ 440MITActualizado hace 14 meses
Instalar

Remote Desktop Commander

de desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Se ejecuta en la nube★ 211Actualizado anteayer
Instalar

README del creador

Abrir el README

Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.

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

Solo se muestra el principio; lee el resto en el repo

Pregunta a PopNx