apply_memory_retention_batch

Atomically apply 1..10 approved items after a trusted internal online backup.

SERVERMapi Agent Memory SOURCEcabo0m/mapi-agent-memory

Medium RISK CLASS

Category Write

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/mapi-agent-memory/apply-memory-retention-batch.md

WHAT IT DOES

What apply_memory_retention_batch does on Mapi Agent Memory

AI agents use apply_memory_retention_batch to create or update resources in Mapi Agent Memory, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Mapi Agent Memory environment.

RISK

Why apply_memory_retention_batch is rated Medium

This tool modifies memory state by applying approved items in batch operations. While the governance framing ("approved", "trusted internal backup") suggests safeguards are in place, the core action is a write operation that changes persisted data.

From the tool's definition Tool applies approved items to memory, with language suggesting batch modification ("apply", "atomically apply").

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs apply_memory_retention_batch safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Mapi Agent Memory, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For apply_memory_retention_batch, this is the rule to start with:

apply_memory_retention_batch Rate-limited

apply_memory_retention_batch 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "apply_memory_retention_batch": {
      "limits": [
        {
          "counter": "apply_memory_retention_batch_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Mapi Agent Memory, apply this rule, and every apply_memory_retention_batch call is checked against it from then on.

FAQ

Questions about apply_memory_retention_batch

What does the apply_memory_retention_batch tool do? +

Atomically apply 1..10 approved items after a trusted internal online backup. It is categorised as a Write tool in the Mapi Agent Memory MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on apply_memory_retention_batch? +

Register the Mapi Agent Memory MCP server in PolicyLayer and add a rule for apply_memory_retention_batch: 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 Mapi Agent Memory. Nothing to install.

What risk level is apply_memory_retention_batch? +

apply_memory_retention_batch is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit apply_memory_retention_batch? +

Yes. Add a rate_limit block to the apply_memory_retention_batch 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.

How do I block apply_memory_retention_batch completely? +

Set action: deny in the PolicyLayer policy for apply_memory_retention_batch. 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.

What MCP server provides apply_memory_retention_batch? +

apply_memory_retention_batch is provided by the Mapi Agent Memory MCP server (cabo0m/mapi-agent-memory). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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