Retrieve previously saved memories from persistent storage. Returns a JSON object with a memories array, each entry containing key, value, and type. Use this at the start of every session to restore context, installed skills, and user preferences. Returns an empty array if no memories exist. Filt...
Risk signalsBulk/mass operation — affects multiple targets
Part of the Loaditout server.
Free to start. No card required.
AI agents invoke recall_memory to trigger processes or run actions in Loaditout. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.
recall_memory can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.
Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.
{
"version": "1",
"default": "deny",
"tools": {
"recall_memory": {
"limits": [
{
"counter": "recall_memory_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}See the full Loaditout policy for all 21 tools.
These attack patterns abuse exactly the kind of access recall_memory gives an agent. Each links to the full case and the policy that stops it:
Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Retrieve previously saved memories from persistent storage. Returns a JSON object with a memories array, each entry containing key, value, and type. Use this at the start of every session to restore context, installed skills, and user preferences. Returns an empty array if no memories exist. Filter by type to retrieve only specific categories of memories.. It is categorised as a Execute tool in the Loaditout MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Loaditout MCP server in PolicyLayer and add a rule for recall_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 Loaditout. Nothing to install.
recall_memory is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the recall_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 recall_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.
recall_memory is provided by the Loaditout MCP server (loaditout-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 21 Loaditout tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
4,600+ MCP servers and 31,000+ tools scanned and risk-classified.