AI agents call search_memory to retrieve information from MCP RAG without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves or queries stored memory data without creating, modifying, or deleting anything. It is a passive read operation that returns search results based on semantic similarity. The verb 'search' and explicit reference to information retrieval clearly classify this as a Read operation.
From the tool's definition Tool name 'search_memory' and description 'Search for relevant information in agent memory' indicate a retrieval operation with no side effects.
Attacks that exploit this kind of access
Search for relevant information in agent memory. It is categorised as a Read tool in the MCP RAG MCP Server, which means it retrieves data without modifying state.
Register the MCP RAG MCP server in PolicyLayer and add a rule for search_memory: 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 RAG. Nothing to install.
search_memory 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 search_memory 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 search_memory. 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.
search_memory is provided by the MCP RAG MCP server (santis84/mcp-rag). 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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