Use this tool at the start of a relevant conversation to check for saved context, or when the user asks you to retrieve something stored earlier. Triggers: 'recall my project notes', 'what did we save last time?', 'look up my preferences', 'fetch the notes you stored'. Also call proactively at th...
Part of the Toolora MCP Server server.
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AI agents invoke recall_memory to trigger processes or run actions in Toolora MCP Server. 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 Toolora MCP Server policy for all 34 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.
Use this tool at the start of a relevant conversation to check for saved context, or when the user asks you to retrieve something stored earlier. Triggers: 'recall my project notes', 'what did we save last time?', 'look up my preferences', 'fetch the notes you stored'. Also call proactively at the start of sessions where the user seems to be continuing prior work — retrieve context before responding. Pass the same key used with save_memory. Returns stored content, save date, and expiry date.. It is categorised as a Execute tool in the Toolora MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Toolora MCP Server 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 Toolora MCP Server. 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 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.
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