Low Risk

token_budget_calculator

Plan token allocation across system prompt, user input, context/RAG chunks, and expected output. Warns if budget exceeds model context window. Supports 25+ models.

Part of the IA-QA — 130+ QA & Dev Tools for AI Agents server.

token_budget_calculator 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 token_budget_calculator to retrieve information from IA-QA — 130+ QA & Dev Tools for AI Agents 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 token_budget_calculator 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": {
    "token_budget_calculator": {}
  }
}

See the full IA-QA — 130+ QA & Dev Tools for AI Agents policy for all 146 tools.

Get this rule live on your own IA-QA — 130+ QA & Dev Tools for AI Agents 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 token_budget_calculator 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 token_budget_calculator 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 token_budget_calculator tool do? +

Plan token allocation across system prompt, user input, context/RAG chunks, and expected output. Warns if budget exceeds model context window. Supports 25+ models.. It is categorised as a Read tool in the IA-QA — 130+ QA & Dev Tools for AI Agents MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on token_budget_calculator? +

Register the IA-QA — 130+ QA & Dev Tools for AI Agents MCP server in PolicyLayer and add a rule for token_budget_calculator: 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 IA-QA — 130+ QA & Dev Tools for AI Agents. Nothing to install.

What risk level is token_budget_calculator? +

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

Can I rate-limit token_budget_calculator? +

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

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

token_budget_calculator is provided by the IA-QA — 130+ QA & Dev Tools for AI Agents MCP server (https://www.ia-qa.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every IA-QA — 130+ QA & Dev Tools for AI Agents tool call.

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