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...
Accepts freeform code/query input (script); High parameter count (12 properties)
Part of the DataGen MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
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. Intercept 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.
tools:
asyncExecuteCode:
rules:
- action: allow
rate_limit:
max: 10
window: 60
validate:
required_args: trueSee the full DataGen policy for all 20 tools.
Agents calling execute-class tools like asyncExecuteCode have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Execute risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.
asyncExecuteCode is one of the high-risk operations in DataGen. For the full severity-focused view — only the high-risk tools with their recommended policies — see the breakdown for this server, or browse all high-risk tools across every MCP server.
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.
Add a rule in your Intercept YAML policy under the tools section for asyncExecuteCode. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the DataGen MCP server.
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 Intercept 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 Intercept 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). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Open source. One binary. Zero dependencies.
npx -y @policylayer/intercept