Submit an LLM request to be processed asynchronously. Returns a job ID immediately that can be used to poll for results later.
AI agents invoke submit-llm-request-async to trigger actions in Cross-LLM 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 triggers an external operation — an asynchronous call to an LLM API — whose effects depend on the arguments provided (prompt, model choice, parameters). It doesn't just read data or write local state; it executes a remote computation/inference request. The severity is medium because misuse could incur API costs or produce unintended LLM outputs, but it doesn't directly destroy data or move money.
From the tool's definition Submit an LLM request to be processed asynchronously... triggers external operations (calling external LLM APIs) and returns a job ID for polling results
Documented attack patterns abuse exactly the kind of access submit-llm-request-async gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Cross-LLM MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for submit-llm-request-async:
{
"version": "1",
"default": "deny",
"tools": {
"submit-llm-request-async": {
"limits": [
{
"counter": "submit-llm-request-async_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}submit-llm-request-async 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 an LLM request to be processed asynchronously. Returns a job ID immediately that can be used to poll for results later. It is categorised as a Execute tool in the Cross-LLM MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Cross-LLM MCP Server MCP server in PolicyLayer and add a rule for submit-llm-request-async: 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 Cross-LLM MCP Server. Nothing to install.
submit-llm-request-async 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-llm-request-async 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-llm-request-async. 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-llm-request-async is provided by the Cross-LLM MCP Server MCP server (jamesanz/cross-llm-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Cross-LLM 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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23 Cross-LLM MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.