Get AI token usage statistics for a project. Shows how many tokens have been consumed by AI translation and quality check operations. Useful for monitoring costs and understanding AI usage patterns.
AI agents call get_ai_usage to retrieve information from Localization without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
projectSlug | string | Yes | Project slug |
Parameters from the server's own tool schema.
This tool retrieves and displays historical usage statistics and cost information. It performs no mutations, executions, financial transactions, or destructive operations. It is purely informational monitoring of past AI consumption metrics. The low severity reflects that misuse would only expose usage data, not cause operational harm or financial impact.
From the tool's definition Tool description states 'Get AI token usage statistics' and 'Shows how many tokens have been consumed'. The verb 'Get' and 'Shows' indicate read-only retrieval of existing data without modification or side effects.
Attacks that exploit this kind of access
Get AI token usage statistics for a project. Shows how many tokens have been consumed by AI translation and quality check operations. Useful for monitoring costs and understanding AI usage patterns. It is categorised as a Read tool in the Localization MCP Server, which means it retrieves data without modifying state.
get_ai_usage accepts 1 parameter: projectSlug. Required: projectSlug. The full parameter table on this page comes from the server's own tool schema.
Register the Localization MCP server in PolicyLayer and add a rule for get_ai_usage: 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 Localization. Nothing to install.
get_ai_usage is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_ai_usage 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.
Set action: deny in the PolicyLayer policy for get_ai_usage. 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.
get_ai_usage is provided by the Localization MCP server (localization-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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