AI agents use memory_store to create or update resources in MemoryClaw — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your MemoryClaw environment.
This tool modifies stored data (memories) in a persistent store, which is a Write operation. The action is reversible (memories can be updated or overwritten without permanent loss). It poses low severity because memories are application-level context data; misuse would not typically cause data loss, financial harm, or external system compromise.
From the tool's definition The tool is described as 'Save or update a memory file in the workspace.' The verbs 'save' and 'update' are characteristic of Write operations—they create or modify data reversibly without deleting or destroying it.
Documented attack patterns abuse exactly the kind of access memory_store gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and MemoryClaw, and nothing reaches the server without passing your rules. This is the rule we recommend for memory_store:
{
"version": "1",
"default": "deny",
"tools": {
"memory_store": {
"limits": [
{
"counter": "memory_store_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}memory_store 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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Save or update a memory file in the workspace. It is categorised as a Write tool in the MemoryClaw MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the MemoryClaw MCP server in PolicyLayer and add a rule for memory_store: 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 MemoryClaw. Nothing to install.
memory_store 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 memory_store 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_store. 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_store is provided by the MemoryClaw MCP server (tostechbr/memoryclaw). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from MemoryClaw, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
6 MemoryClaw tools catalogued and risk-classified — across an index of 43,000+ MCP servers.