AI agents call memory_recall to retrieve information from Tartarus 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 memories by topic, which is a read-only operation. No data is modified, deleted, or executed. The action is passive retrieval of previously stored information from a local SQLite-backed memory store, making it a straightforward Read category tool with low severity.
From the tool's definition Tool name 'memory_recall' and description 'Retrieve memories by topic' indicate a retrieval operation with no side effects.
Attacks that exploit this kind of access
Retrieve memories by topic. It is categorised as a Read tool in the Tartarus MCP Server, which means it retrieves data without modifying state.
Register the Tartarus MCP server in PolicyLayer and add a rule for memory_recall: 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 Tartarus. Nothing to install.
memory_recall 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 memory_recall 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 memory_recall. 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.
memory_recall is provided by the Tartarus MCP server (saluca-labs/tartarus-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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