AI agents use update_memory to create or update resources in Robust Long-Term Memory MCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Robust Long-Term Memory MCP environment.
This tool creates or modifies data (memories) in a reversible manner—an agent could update memory entries but the changes are not permanent/irreversible deletions. The empty description prevents full certainty, but the context of a memory management system with explicit delete and update functions clearly places this in the Write category rather than Read (it modifies, not just retrieves) or Destructive (changes are…
From the tool's definition Tool named 'update_memory' is a sibling to 'delete_memory', 'remember', and 'search_memories' on a persistent memory system using SQLite and ChromaDB.
Documented attack patterns abuse exactly the kind of access update_memory gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Robust Long-Term Memory MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for update_memory:
{
"version": "1",
"default": "deny",
"tools": {
"update_memory": {
"limits": [
{
"counter": "update_memory_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}update_memory stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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update_memory. It is categorised as a Write tool in the Robust Long-Term Memory MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Robust Long-Term Memory 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 Robust Long-Term Memory MCP. 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 Robust Long-Term Memory MCP server (rotoslider/long-term-memory-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 11 Robust Long-Term Memory MCP tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
11 Robust Long-Term Memory MCP tools catalogued and risk-classified — across an index of 42,500+ MCP servers.