answer_query
Use answer_query to get a grounded answer to a query about Google developer products. This tool has limited quota. This tool will synthesize information from the corpus to generate an answer to the query. answer_query grounds answers using the same corpus as search_documents. This tool returns th...
This record as markdown: /tools/com-googleapis-developerknowledge-mcp/answer-query.md
What answer_query does on Mcp
AI agents call answer_query to retrieve information from Mcp without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
query | string | Yes | Required. The query to answer. |
Parameters from the server's own tool schema.
Why answer_query is rated Low
This tool retrieves and synthesizes existing information from a read-only documentation corpus. It has no capability to modify data, execute code, delete resources, or perform financial transactions. The 'limited quota' constraint is a rate-limiting measure, not a capability indicator. The tool's purpose is purely informational retrieval, making it a Read operation with low severity risk.
From the tool's definition Tool description states it 'get[s] a grounded answer' and 'synthesize[s] information from the corpus to generate an answer.' The tool returns 'the generated answer_text and a list of document names' from Google's public developer documentation without…
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs answer_query safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For answer_query, this is the rule to start with:
answer_query is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mcp, apply this rule, and every answer_query call is checked against it from then on.
Questions about answer_query
Use answer_query to get a grounded answer to a query about Google developer products. This tool has limited quota. This tool will synthesize information from the corpus to generate an answer to the query. answer_query grounds answers using the same corpus as search_documents. This tool returns the generated answer_text and a list of document names (references) used to generate the answer. Use get_documents with the document names to fetch the entire document content if needed. If you get a 429 out of quota error, use search_documents instead. It is categorised as a Read tool in the Mcp MCP Server, which means it retrieves data without modifying state.
answer_query accepts 1 parameter: query. Required: query. The full parameter table on this page comes from the server's own tool schema.
Register the MCP server in PolicyLayer and add a rule for answer_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 Mcp. Nothing to install.
answer_query 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 answer_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 answer_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.
answer_query is provided by the MCP server (https://developerknowledge.googleapis.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
More on , and thousands of servers like it.
This server
Across the catalogue