Low Risk

estimate_cost

Estimate the cost of an AI API call given model and token counts or text. Returns input/output/total cost and optional monthly projection.

Part of the Ai Token Counter server.

estimate_cost 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 estimate_cost to retrieve information from Ai Token Counter 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 estimate_cost 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": {
    "estimate_cost": {}
  }
}

See the full Ai Token Counter policy for all 4 tools.

Get this rule live on your own Ai Token Counter 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 estimate_cost 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 estimate_cost 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 estimate_cost tool do? +

Estimate the cost of an AI API call given model and token counts or text. Returns input/output/total cost and optional monthly projection.. It is categorised as a Read tool in the Ai Token Counter MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on estimate_cost? +

Register the Ai Token Counter MCP server in PolicyLayer and add a rule for estimate_cost: 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 Token Counter. Nothing to install.

What risk level is estimate_cost? +

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

Can I rate-limit estimate_cost? +

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

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

estimate_cost is provided by the Ai Token Counter MCP server (https://api.lazy-mac.com/ai-token-counter/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Ai Token Counter tool call.

Deterministic rules across all 4 Ai Token Counter tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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