Query the RAG system with a question. Optionally filter by tags and/or section path. The system will retrieve relevant context and generate an answer using Google AI Studio.
AI agents call query_rag to retrieve information from RAG Document Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool retrieves and queries data from the RAG index without any side effects. It reads documents, performs semantic search, and generates responses—typical of Read operations. The optional filtering by tags and section path are query parameters that refine retrieval only. No data is created, modified, deleted, or executed as a result of using this tool.
From the tool's definition Tool description states 'Query the RAG system with a question' and 'retrieve relevant context and generate an answer'. No modification, deletion, or execution of external operations mentioned.
Attacks that exploit this kind of access
Query the RAG system with a question. Optionally filter by tags and/or section path. The system will retrieve relevant context and generate an answer using Google AI Studio. It is categorised as a Read tool in the RAG Document Server MCP Server, which means it retrieves data without modifying state.
Register the RAG Document Server MCP server in PolicyLayer and add a rule for query_rag: 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 RAG Document Server. Nothing to install.
query_rag 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_rag 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_rag. 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_rag is provided by the RAG Document Server MCP server (jaimeferj/mcp-rag-docs). 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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