memory_recall
AI agents call memory_recall to retrieve information from Memory-MCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Memory recall is a read operation that queries stored data using vector embeddings and BM25 search. It has no side effects, does not modify or delete data, and poses minimal security risk if misused by an agent—the worst outcome would be retrieving unintended memories. This is characteristic of Read category tools.
From the tool's definition Tool name 'memory_recall' with empty description suggests retrieval functionality consistent with sibling tools like 'memory_recall_project' and 'memory_save'.
Attacks that exploit this kind of access
memory_recall. It is categorised as a Read tool in the Memory-MCP MCP Server, which means it retrieves data without modifying state.
Register the Memory- 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 Memory-MCP. 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 Memory- MCP server (wb200/memory-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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