AI agents invoke start_game to trigger actions in Lemonade Stand MCP Server. 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.
This tool triggers initialization of a game environment, which is an external operation execution. While the outcome is deterministic (starting a game), it is fundamentally an Execute action because it runs a process with state-changing side effects. The severity is low because the game is sandboxed (a simulation) and carries no real financial, data destruction, or system security risks.
From the tool's definition 'Start a new lemonade stand game' — initiates game state and triggers an external operation whose effects depend on game mechanics and agent decisions
Documented attack patterns abuse exactly the kind of access start_game gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Lemonade Stand MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for start_game:
{
"version": "1",
"default": "deny",
"tools": {
"start_game": {
"limits": [
{
"counter": "start_game_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}start_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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Start a new lemonade stand game. It is categorised as a Execute tool in the Lemonade Stand MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Lemonade Stand MCP Server MCP server in PolicyLayer and add a rule for start_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 Lemonade Stand MCP Server. Nothing to install.
start_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 start_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 start_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.
start_game is provided by the Lemonade Stand MCP Server MCP server (jimmcq/lemonade-stand-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Lemonade Stand MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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5 Lemonade Stand MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.