query_model · Ai Analyst MCP: Risk & Policy

WHAT IT DOES

What query_model does on Ai Analyst

AI agents invoke query_model to trigger actions in Ai Analyst. 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.

WHY IT NEEDS A POLICY

Why query_model needs a policy

The tool name 'query_model' suggests executing a query against a data model. Given the server context ('natural language data queries', 'analytical tools for product analytics') and sibling tools like 'execute_workflow' and 'run_query'-style operations, this likely executes queries that may have side effects depending on arguments. Empty description lowers confidence.

From the tool's definition Tool name is 'query_model'; description is empty or uninformative.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

query_model Rate-limited

query_model 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "query_model": {
      "limits": [
        {
          "counter": "query_model_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Ai Analyst, so you can run agents against it safely.

FAQ

Questions about query_model

What does the query_model tool do? +

query_model. It is categorised as a Execute tool in the Ai Analyst MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on query_model? +

Register the Ai Analyst MCP server in PolicyLayer and add a rule for query_model: 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 Ai Analyst. Nothing to install.

What risk level is query_model? +

query_model is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit query_model? +

Yes. Add a rate_limit block to the query_model 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.

How do I block query_model completely? +

Set action: deny in the PolicyLayer policy for query_model. 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.

What MCP server provides query_model? +

query_model is provided by the Ai Analyst MCP server (sbdk-dev/local-ai-analyst). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.