GCP Billing — summary and by-service cost breakdown via BigQuery billing export.
AI agents call gcp_billing to retrieve information from RedisNexus without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool retrieves and summarizes GCP billing data from BigQuery exports. It reads financial information but does not move money, commit financial obligations, or modify any data. However, it exposes sensitive financial cost data, warranting a medium severity rating due to potential data leakage of cost structures and usage patterns.
From the tool's definition summary and by-service cost breakdown via BigQuery billing export
Attacks that exploit this kind of access
GCP Billing — summary and by-service cost breakdown via BigQuery billing export. It is categorised as a Read tool in the RedisNexus MCP Server, which means it retrieves data without modifying state.
Register the RedisNexus MCP server in PolicyLayer and add a rule for gcp_billing: 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 RedisNexus. Nothing to install.
gcp_billing 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 gcp_billing 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 gcp_billing. 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.
gcp_billing is provided by the RedisNexus MCP server (rajkumar-madhu/mcp). 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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