AI agents use update_memory to create or update resources in Mem0 — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Mem0 environment.
This tool creates or modifies data reversibly by updating memory entries in the Mem0 AsyncMemory system. While the description is empty, the name and context from sibling tools clearly indicate Write category semantics.
From the tool's definition Tool name 'update_memory' indicates modification of stored memory data. Sibling tools include 'add_memory', 'delete_memory', and 'get_memory', establishing this as part of a memory management API.
Attacks that exploit this kind of access
update_memory. It is categorised as a Write tool in the Mem0 MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Mem0 MCP server in PolicyLayer and add a rule for update_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 Mem0. Nothing to install.
update_memory is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the update_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 update_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.
update_memory is provided by the Mem0 MCP server (olk/mem0-mcp-server). 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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