Low Risk

stats_hurst-exponent

Hurst exponent via rescaled range (R/S) analysis. Use when determining if a time series is mean-reverting (H<0.5), random walk (H=0.5), or trending (H>0.5). Provide a price or return series. Returns: Hurst exponent via R/S analysis, classification, and confidence.

Part of the Quantoracle server.

stats_hurst-exponent is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call stats_hurst-exponent to retrieve information from Quantoracle without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though stats_hurst-exponent only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "stats_hurst-exponent": {}
  }
}

See the full Quantoracle policy for all 74 tools.

Get this rule live on your own Quantoracle server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access stats_hurst-exponent gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so stats_hurst-exponent only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the stats_hurst-exponent tool do? +

Hurst exponent via rescaled range (R/S) analysis. Use when determining if a time series is mean-reverting (H<0.5), random walk (H=0.5), or trending (H>0.5). Provide a price or return series. Returns: Hurst exponent via R/S analysis, classification, and confidence.. It is categorised as a Read tool in the Quantoracle MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on stats_hurst-exponent? +

Register the Quantoracle MCP server in PolicyLayer and add a rule for stats_hurst-exponent: 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 Quantoracle. Nothing to install.

What risk level is stats_hurst-exponent? +

stats_hurst-exponent is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit stats_hurst-exponent? +

Yes. Add a rate_limit block to the stats_hurst-exponent 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 stats_hurst-exponent completely? +

Set action: deny in the PolicyLayer policy for stats_hurst-exponent. 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 stats_hurst-exponent? +

stats_hurst-exponent is provided by the Quantoracle MCP server (QuantOracle/quantoracle). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Quantoracle tool call.

Deterministic rules across all 74 Quantoracle tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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