Submit a SAS job for asynchronous execution via the Job Execution service.
AI agents invoke submit_batch_job to trigger actions in SAS MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool submits and executes SAS code/jobs in a remote compute environment. Execution of arbitrary SAS programs can have wide-ranging side effects including data manipulation, file I/O, network calls, or database operations depending on the submitted code. It is an Execute-category action (not merely Read or Write) because it triggers external computation whose effects depend on the job content.
From the tool's definition Submit a SAS job for asynchronous execution via the Job Execution service
Documented attack patterns abuse exactly the kind of access submit_batch_job gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and SAS MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for submit_batch_job:
{
"version": "1",
"default": "deny",
"tools": {
"submit_batch_job": {
"limits": [
{
"counter": "submit_batch_job_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}submit_batch_job stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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Submit a SAS job for asynchronous execution via the Job Execution service. It is categorised as a Execute tool in the SAS MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the SAS MCP Server MCP server in PolicyLayer and add a rule for submit_batch_job: 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 SAS MCP Server. Nothing to install.
submit_batch_job 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 submit_batch_job 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 submit_batch_job. 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.
submit_batch_job is provided by the SAS MCP Server MCP server (sassoftware/sas-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from SAS MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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27 SAS MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.