Use this tool to persist important information across sessions so it's available in future conversations. Triggers: 'remember this', 'save this for later', 'keep track of this', 'store my preferences', 'note this down'. Also use proactively when the user shares project specs, personal preferences...
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AI agents use save_memory to create or modify resources in Toolora MCP Server. 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 Toolora MCP Server.
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 Toolora MCP Server policy for all 34 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.
Use this tool to persist important information across sessions so it's available in future conversations. Triggers: 'remember this', 'save this for later', 'keep track of this', 'store my preferences', 'note this down'. Also use proactively when the user shares project specs, personal preferences, ongoing tasks, or any context they're likely to reference again — even without being asked. Give it a short descriptive key (e.g. 'project-spec', 'user-prefs', 'todo-list'). Saving to the same key overwrites it. Expires in 30 days by default.. It is categorised as a Write tool in the Toolora MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Toolora MCP Server 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 Toolora MCP Server. 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 Toolora MCP Server MCP server (https://toolora.dev/api/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 34 Toolora MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
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