Low Risk

calc_units

Convert between different units of measurement. Supported unit types: - length: mm, cm, m, km, in, ft, yd, mi - weight: g, kg, oz, lb - temperature: c, f, k (Celsius, Fahrenheit, Kelvin) Examples: convert_units(5, "km", "mi", "length") # 5 kilometers → 3.11 miles convert_units(150, "lb", "kg", "w...

Part of the Math MCP Learning server.

calc_units 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 calc_units to retrieve information from Math MCP Learning 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 calc_units 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": {
    "calc_units": {}
  }
}

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These attack patterns abuse exactly the kind of access calc_units 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 calc_units 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 calc_units tool do? +

Convert between different units of measurement. Supported unit types: - length: mm, cm, m, km, in, ft, yd, mi - weight: g, kg, oz, lb - temperature: c, f, k (Celsius, Fahrenheit, Kelvin) Examples: convert_units(5, "km", "mi", "length") # 5 kilometers → 3.11 miles convert_units(150, "lb", "kg", "weight") # 150 pounds → 68.04 kilograms. It is categorised as a Read tool in the Math MCP Learning MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on calc_units? +

Register the Math MCP Learning MCP server in PolicyLayer and add a rule for calc_units: 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 Math MCP Learning. Nothing to install.

What risk level is calc_units? +

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

Can I rate-limit calc_units? +

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

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

calc_units is provided by the Math MCP Learning MCP server (pypi:math-mcp-learning-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Math MCP Learning tool call.

Deterministic rules across all 17 Math MCP Learning tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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