AI agents call get_tables to retrieve information from Bq without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and returns table metadata from BigQuery without modifying data. It is a retrieval operation with no side effects, fitting the Read category. Severity is low because metadata queries have minimal blast radius even if called inappropriately by an AI agent.
From the tool's definition Tool name 'get_tables' indicates data retrieval; server description states it 'retrieves and caches BigQuery metadata (datasets, tables, columns)'; sibling tools include 'get_datasets' and 'search_metadata' which are clearly read operations.
Attacks that exploit this kind of access
get_tables. It is categorised as a Read tool in the Bq MCP Server, which means it retrieves data without modifying state.
Register the Bq MCP server in PolicyLayer and add a rule for get_tables: 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 Bq. Nothing to install.
get_tables 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_tables 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_tables. 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_tables is provided by the Bq MCP server (takada-at/bq_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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