AI agents invoke stop_game to trigger actions in Unity-MCP. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
stop_game performs an action (halting execution) rather than reading data. It is not reversible in the sense that state between stop and restart may differ, and it externally affects the Unity runtime. This qualifies as Execute rather than Write (which is for reversible creation/modification).
From the tool's definition Tool name 'stop_game' indicates it triggers termination of a running game environment. The server description confirms this is a 'bridge between Unity and AI assistants' for 'code execution' and 'runtime debugging.' Stopping a game is an external operation…
Documented attack patterns abuse exactly the kind of access stop_game gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Unity-MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for stop_game:
{
"version": "1",
"default": "deny",
"tools": {
"stop_game": {
"limits": [
{
"counter": "stop_game_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}stop_game stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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stop_game. It is categorised as a Execute tool in the Unity-MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Unity- MCP server in PolicyLayer and add a rule for stop_game: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Unity-MCP. Nothing to install.
stop_game is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the stop_game rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for stop_game. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
stop_game is provided by the Unity- MCP server (tsavo/unity-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Unity-MCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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7 Unity-MCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.