AI agents call check_pet to retrieve information from MCPet without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves the current state of a virtual pet (status, health, mood, etc.) without modifying, executing external operations, or causing irreversible changes. It is purely informational, making it a Read category tool with low severity.
From the tool's definition Tool name 'check_pet' and description 'Check on your virtual pet' indicate a query/status-checking operation with no side effects.
Documented attack patterns abuse exactly the kind of access check_pet gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and MCPet, and nothing reaches the server without passing your rules. This is the rule we recommend for check_pet:
{
"version": "1",
"default": "deny",
"tools": {
"check_pet": {}
}
}check_pet is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Check on your virtual pet. It is categorised as a Read tool in the MCPet MCP Server, which means it retrieves data without modifying state.
Register the MCPet MCP server in PolicyLayer and add a rule for check_pet: 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 MCPet. Nothing to install.
check_pet is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the check_pet 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 check_pet. 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.
check_pet is provided by the MCPet MCP server (shreyaskarnik/mcpet). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from MCPet, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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6 MCPet tools catalogued and risk-classified — across an index of 43,000+ MCP servers.