Execute Python code asynchronously for long-running operations. This tool starts Python code execution in the background and returns immediately with an execution UUID. Use 'checkCodeExecStatus' to monitor progress and retrieve results. Perfect for long-running scripts, large data processing, or ...
Risk signalsAccepts freeform code/query input (script) · High parameter count (12 properties)
Part of the DataGen server.
Free to start. No card required.
AI agents invoke asyncExecuteCode to trigger processes or run actions in DataGen. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.
asyncExecuteCode can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.
Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.
{
"version": "1",
"default": "deny",
"tools": {
"asyncExecuteCode": {
"limits": [
{
"counter": "asyncexecutecode_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}See the full DataGen policy for all 20 tools.
These attack patterns abuse exactly the kind of access asyncExecuteCode gives an agent. Each links to the full case and the policy that stops it:
Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Execute Python code asynchronously for long-running operations. This tool starts Python code execution in the background and returns immediately with an execution UUID. Use 'checkCodeExecStatus' to monitor progress and retrieve results. Perfect for long-running scripts, large data processing, or operations that might take several minutes. call this tool when you are dealing with long running operations. Key advantages over executeCode: - Non-blocking execution - No timeout limitations Workflow: 1. Call this tool to start execution 2. Get execution_uuid in response 3. Use 'checkCodeExecStatus' to monitor progress 4. Retrieve results when status is 'completed' Do not use any local() or global() in the code. Do not use any async in the code. it will cause the code to not work. When work with API directly, use httpx instead of requests.. It is categorised as a Execute tool in the DataGen MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the DataGen MCP server in PolicyLayer and add a rule for asyncExecuteCode: 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 DataGen. Nothing to install.
asyncExecuteCode 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 asyncExecuteCode 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 asyncExecuteCode. 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.
asyncExecuteCode is provided by the DataGen MCP server (kuoyusheng/datagendev). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 20 DataGen tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
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