mcp-gatehouse

# mcp-gatehouse

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**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](https://github.com/modelcontextprotocol/python-sdk).

```
pip install mcp-gatehouse
```

## What you get

| | |
|---|---|
| **Permission tiers** | Every 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 gates** | Tiers you choose require a sign-off before the tool runs. Your approver is any callable — a terminal prompt, a Slack ping, a ticket. **Fails closed:** a gated tool with no approver configured is denied, not waved through. |
| **Audit log** | Append-only JSONL, one line per call — allowed, denied, or failed — with UTC timestamps and durations. The answer to "what did the AI actually do?" six months later. |
| **Redaction** | Argument keys you name (`api_key`, `password`, `token`, … by default) are masked before they reach the log *or* the approver. |
| **Denylist** | Block a tool outright, whatever its tier. |

## Quickstart

```python
from mcp.server.mcpserver import MCPServer
from mcp_gatehouse import AccessTier, AuditLog, Gatehouse, Policy

mcp = MCPServer("order-desk")
gatehouse = Gatehouse(
    mcp,
    policy=Policy(approver=lambda req: input(f"allow {req.tool}? [y/N] ") == "y"),
    audit=AuditLog(path="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,
transports, and everything else work unchanged — the guard preserves the
function's signature.

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

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

What the audit trail looks like:

```json
{"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"}}
```

## Try the demo

The package ships a runnable order-desk server with all three tiers wired
up and a terminal-prompt approver:

```
mcp-gatehouse-demo
```

Point any MCP client at it over stdio (Claude Desktop, etc.), ask the model
to cancel an order, and watch the approval land in your terminal — and the
verdict land in `audit.jsonl` either way. `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 few
  small classes and a JSONL file.
- **Fail closed.** Security defaults that quietly allow are worse than none.
  That includes redaction: argument values the scrubber can't take apart
  (arbitrary objects, bytes) are replaced with an opaque placeholder rather
  than passed through, and exception *messages* stay out of the log —
  only the exception type is recorded, because error text loves to embed
  the very values you just redacted.
- **The audit log records denials and errors**, not just successes — the
  calls that *didn't* happen are half the story.
- **A blocking terminal approver and the stdio transport don't mix** —
  stdout/stdin are the protocol pipe. The demo's approver prompts on
  `/dev/tty` for exactly that reason (and denies when no terminal exists).
  Real deployments should approve out-of-band: Slack, a ticket, a queue.
- **What this is not:** authentication, transport encryption, or a sandbox.
  It's a gate inside your server, not a perimeter around it. See
  [SECURITY.md](SECURITY.md).

## Compatibility

Targets the official [`mcp` Python SDK](https://github.com/modelcontextprotocol/python-sdk)
v2.x (`mcp>=2,<3`) and Python 3.10+.

| `mcp-gatehouse` | SDK | Server class |
|---|---|---|
| `0.2.x` | `mcp>=2,<3` | `MCPServer` |
| `0.1.x` | `mcp>=1.27,<2` | `FastMCP` |

The public API (`Gatehouse`, `Policy`, `AuditLog`, `AccessTier`) is
unchanged across that line, as promised. Porting a v1 server is two
import edits — `FastMCP` became `MCPServer` and moved to
`mcp.server.mcpserver`; see the SDK's
[migration guide](https://py.sdk.modelcontextprotocol.io/v2/migration/).

Staying on SDK v1 needs no action: `0.1.x` pins `mcp<2`, so pip keeps
resolving it. That line is closed to features but still gets security
fixes.

## Who built this

[Nick George](https://nickgeorgeai.com) — I design and run MCP servers in
production for a mid-market reverse logistics-tech company, and build them
for businesses at [nickgeorgeai.com](https://nickgeorgeai.com). This
library is the permission-and-audit discipline from those builds, extracted.

If you're an owner or operator wondering what MCP even is, start with the
plain-English guide: [What is an MCP server?](https://nickgeorgeai.com/mcp)

## License

[MIT](LICENSE)