Check if an action is allowed by the organization's policies.
AI agents call check_policy to retrieve information from Pypi:asqav without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs a read-only check against stored policies to determine authorization. It does not create, modify, delete, or execute any action—it only evaluates and returns policy compliance information. The function is informational (Read category).
From the tool's definition Tool name 'check_policy' and description 'Check if an action is allowed' indicate a query/lookup operation that retrieves policy enforcement status without modifying data or executing external actions.
Documented attack patterns abuse exactly the kind of access check_policy gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Pypi:asqav, and nothing reaches the server without passing your rules. This is the rule we recommend for check_policy:
{
"version": "1",
"default": "deny",
"tools": {
"check_policy": {}
}
}check_policy is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Check if an action is allowed by the organization's policies. It is categorised as a Read tool in the Pypi:asqav MCP Server, which means it retrieves data without modifying state.
Register the Pypi:asqav MCP server in PolicyLayer and add a rule for check_policy: 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 Pypi:asqav. Nothing to install.
check_policy 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_policy 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_policy. 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_policy is provided by the Pypi:asqav MCP server (jagmarques/asqav-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Pypi:asqav, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
15 Pypi:asqav tools catalogued and risk-classified — across an index of 43,000+ MCP servers.