Save a key-value pair to persistent agent memory that survives across sessions. Returns a confirmation with the stored key. Use this to remember installed skills, user preferences, project context, or recent search queries. Call this proactively whenever you learn something worth remembering. Do ...
Part of the Loaditout server.
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AI agents use save_memory to create or modify resources in Loaditout. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call save_memory repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Loaditout.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"save_memory": {
"limits": [
{
"counter": "save_memory_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Loaditout policy for all 21 tools.
These attack patterns abuse exactly the kind of access save_memory gives an agent. Each links to the full case and the policy that stops it:
Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Save a key-value pair to persistent agent memory that survives across sessions. Returns a confirmation with the stored key. Use this to remember installed skills, user preferences, project context, or recent search queries. Call this proactively whenever you learn something worth remembering. Do not store sensitive data like passwords or API keys. Retrieve saved memories with recall_memory.. It is categorised as a Write tool in the Loaditout MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Loaditout MCP server in PolicyLayer and add a rule for save_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.
save_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 save_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 save_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.
save_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.
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