AI agents use store_memory to create or update resources in Memlord — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Memlord environment.
The name 'store_memory' strongly implies writing/creating a new memory entry in the server. Given the sibling tools (get_memory, list_memories, update_memory, delete_memory), this tool likely handles initial creation of memory records. Empty description reduces confidence but the naming convention aligns clearly with a Write operation.
From the tool's definition Tool name: store_memory — 'store' implies creating/persisting new data. Description is empty and uninformative, lowering confidence.
Documented attack patterns abuse exactly the kind of access store_memory gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Memlord, and nothing reaches the server without passing your rules. This is the rule we recommend for store_memory:
{
"version": "1",
"default": "deny",
"tools": {
"store_memory": {
"limits": [
{
"counter": "store_memory_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}store_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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store_memory. It is categorised as a Write tool in the Memlord MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Memlord MCP server in PolicyLayer and add a rule for store_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 Memlord. Nothing to install.
store_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 store_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 store_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.
store_memory is provided by the Memlord MCP server (myrikld/memlord). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Memlord, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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10 Memlord tools catalogued and risk-classified — across an index of 43,000+ MCP servers.