Provides a detailed explanation for a query about a specific software topic by synthesizing information primarily from official documentation found via web search. Focuses on comprehensive answers, context, and adherence to documented details. Uses the configured Vertex AI model (${modelIdPlaceho...
AI agents call explain_topic_with_docs to retrieve information from Google AI Search MCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs information retrieval and synthesis from documentation and web search results. It does not create, modify, delete, execute code, or trigger external operations. It is purely a Read operation that queries and retrieves existing data to generate explanatory responses. There is no capability to alter state or execute arbitrary commands.
From the tool's definition Tool description states it 'provides a detailed explanation' and 'synthesizing information primarily from official documentation found via web search.' The verb 'Provides' and 'synthesizing' indicate data retrieval and querying operations.
Attacks that exploit this kind of access
Provides a detailed explanation for a query about a specific software topic by synthesizing information primarily from official documentation found via web search. Focuses on comprehensive answers, context, and adherence to documented details. Uses the configured Vertex AI model (${modelIdPlaceholder}) with Google Search. Requires. It is categorised as a Read tool in the Google AI Search MCP MCP Server, which means it retrieves data without modifying state.
Register the Google AI Search MCP server in PolicyLayer and add a rule for explain_topic_with_docs: 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 AI Search MCP. Nothing to install.
explain_topic_with_docs 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 explain_topic_with_docs 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 explain_topic_with_docs. 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.
explain_topic_with_docs is provided by the Google AI Search MCP server (shariqriazz/google-ai-search-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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