run_feature_usage_analysis · Ai Analyst MCP: Risk & Policy

WHAT IT DOES

What run_feature_usage_analysis does on Ai Analyst

AI agents invoke run_feature_usage_analysis 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 run_feature_usage_analysis needs a policy

The 'run_' prefix and context of an analytics server indicate this tool triggers execution of a pre-defined or parameterized analysis workflow. While it appears to operate on read-only data (feature usage metrics), executing analytical jobs can consume resources and may have indirect side effects (cache invalidation, report generation, etc.).

From the tool's definition Tool name 'run_feature_usage_analysis' indicates execution of an analytical operation. The description is empty, but the sibling tools include 'execute_workflow' and 'execute_script'-like operations, and the server enables 'natural language data queries' with…

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

run_feature_usage_analysis Rate-limited

run_feature_usage_analysis 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": {
    "run_feature_usage_analysis": {
      "limits": [
        {
          "counter": "run_feature_usage_analysis_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 run_feature_usage_analysis

What does the run_feature_usage_analysis tool do? +

run_feature_usage_analysis. 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 run_feature_usage_analysis? +

Register the Ai Analyst MCP server in PolicyLayer and add a rule for run_feature_usage_analysis: 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 run_feature_usage_analysis? +

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

Can I rate-limit run_feature_usage_analysis? +

Yes. Add a rate_limit block to the run_feature_usage_analysis 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 run_feature_usage_analysis completely? +

Set action: deny in the PolicyLayer policy for run_feature_usage_analysis. 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 run_feature_usage_analysis? +

run_feature_usage_analysis 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.