Ask Grok
AI agents invoke llm_query to trigger actions in FGD Fusion Stack Pro. 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 sends a query to an external LLM service (Grok), which constitutes triggering an external operation. The effects depend on the arguments passed (the query content). It is not a simple local read, as it initiates an outbound API call to a third-party service.
From the tool's definition Tool name 'llm_query' and description 'Ask Grok' — triggers an external operation by sending a query to an external LLM provider (Grok/xAI API).
Attacks that exploit this kind of access
Ask Grok. It is categorised as a Execute tool in the FGD Fusion Stack Pro MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the FGD Fusion Stack Pro MCP server in PolicyLayer and add a rule for llm_query: 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 FGD Fusion Stack Pro. Nothing to install.
llm_query 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 llm_query 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 llm_query. 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.
llm_query is provided by the FGD Fusion Stack Pro MCP server (mikeychann-hash/mcpm). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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