AI agents call check_async_status to retrieve information from Openapi Mcp Sdk without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and retrieves the status of a previously initiated asynchronous request. It performs only a read operation without modifying, deleting, or executing any actions. The tool accesses state information about an ongoing operation but does not change that state or trigger new operations.
From the tool's definition Tool name 'check_async_status' and description 'Show the last status of an async request' indicate retrieval of status information with no side effects.
Documented attack patterns abuse exactly the kind of access check_async_status gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Openapi Mcp Sdk, and nothing reaches the server without passing your rules. This is the rule we recommend for check_async_status:
{
"version": "1",
"default": "deny",
"tools": {
"check_async_status": {}
}
}check_async_status is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Show the last status of an async request. It is categorised as a Read tool in the Openapi Mcp Sdk MCP Server, which means it retrieves data without modifying state.
Register the Openapi Mcp Sdk MCP server in PolicyLayer and add a rule for check_async_status: 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 Openapi Mcp Sdk. Nothing to install.
check_async_status 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_async_status 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_async_status. 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_async_status is provided by the Openapi Mcp Sdk MCP server (openapi/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Openapi Mcp Sdk, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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41 Openapi Mcp Sdk tools catalogued and risk-classified — across an index of 43,000+ MCP servers.