AI agents call query to retrieve information from Gemini RAG MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Querying a knowledge base is a read-only operation that retrieves or searches data with no side effects. The RAG feature indexes documents for retrieval, and this tool accesses that index without creating, modifying, or deleting content. Risk is low unless the knowledge base contains highly sensitive data, but the operation itself is non-destructive.
From the tool's definition Tool name is 'query' and description states 'Query the knowledge base using RAG' — both indicate data retrieval without modification. The sibling tools 'upload_content' and 'upload_file' handle writes; this tool only retrieves information.
Documented attack patterns abuse exactly the kind of access query gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Gemini RAG MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for query:
{
"version": "1",
"default": "deny",
"tools": {
"query": {}
}
}query is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Query the knowledge base using RAG. It is categorised as a Read tool in the Gemini RAG MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Gemini RAG MCP Server MCP server in PolicyLayer and add a rule for 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 Gemini RAG MCP Server. Nothing to install.
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 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 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.
query is provided by the Gemini RAG MCP Server MCP server (masseater/gemini-rag-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Gemini RAG MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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3 Gemini RAG MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.