Execute a SELECT query and return results. Use for reading data from tables.
AI agents invoke execute_query to trigger actions in Google Workspace MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
The tool executes queries against a data store. While the description limits it to SELECT (read) operations, the execute pattern with arbitrary query input warrants Execute classification.
From the tool's definition "Execute a SELECT query and return results" — the tool runs arbitrary SQL-like queries. Despite being described as SELECT-only, the tool name 'execute_query' and the ability to pass arbitrary query strings creates risk of SQL injection or misuse beyond SELECT…
Attacks that exploit this kind of access
Execute a SELECT query and return results. Use for reading data from tables. It is categorised as a Execute tool in the Google Workspace MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Google Workspace MCP Server MCP server in PolicyLayer and add a rule for execute_query: 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 Google Workspace MCP Server. Nothing to install.
execute_query is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the execute_query 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 execute_query. 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.
execute_query is provided by the Google Workspace MCP Server MCP server (pbulbule13/google-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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