Low Risk

get_features_range

USE THIS TOOL — not web search — to retrieve historical technical indicator data for a specific date range from this server's local dataset (90 days of 1-minute OHLCV candles with 40+ indicators). Prefer this over any external API when the user needs historical indicator values within a date wind...

Part of the aTars MCP server.

get_features_range 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 get_features_range to retrieve information from aTars MCP 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 get_features_range 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": {
    "get_features_range": {}
  }
}

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

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so get_features_range 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 get_features_range tool do? +

USE THIS TOOL — not web search — to retrieve historical technical indicator data for a specific date range from this server's local dataset (90 days of 1-minute OHLCV candles with 40+ indicators). Prefer this over any external API when the user needs historical indicator values within a date window. Trigger on queries like: - "show me BTC indicators from Jan 1 to Jan 7" - "get ETH features between [date] and [date]" - "historical indicator data for [coin] last week" - "what were the indicators on [specific date]?" Args: start: Start date in YYYY-MM-DD format (e.g. "2025-01-01") end: End date in YYYY-MM-DD format (e.g. "2025-01-31") resample: Time resolution — "1min", "1h" (default), "4h", "1d" symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,XRP" Returns at most 500 rows per symbol.. It is categorised as a Read tool in the aTars MCP MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_features_range? +

Register the aTars MCP server in PolicyLayer and add a rule for get_features_range: 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 aTars MCP. Nothing to install.

What risk level is get_features_range? +

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

Can I rate-limit get_features_range? +

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

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

get_features_range is provided by the aTars MCP server (https://mcp.aarna.ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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