apply_memory_retention_review

Atomically apply one approved and fresh retention review item.

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-review.md

WHAT IT DOES

What apply_memory_retention_review does on Mapi Agent Memory

AI agents use apply_memory_retention_review 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_review is rated Medium

This tool creates or modifies data (retention review configurations/states) in a reversible manner consistent with Write category. It does not delete data (Destructive), execute arbitrary code (Execute), or move money (Financial).

From the tool's definition Tool description states 'Atomically apply one approved and fresh retention review item.' The verb 'apply' combined with 'retention review' indicates the tool modifies memory retention policies or configurations.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs apply_memory_retention_review 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_review, this is the rule to start with:

apply_memory_retention_review Rate-limited

apply_memory_retention_review 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_review": {
      "limits": [
        {
          "counter": "apply_memory_retention_review_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_review call is checked against it from then on.

FAQ

Questions about apply_memory_retention_review

What does the apply_memory_retention_review tool do? +

Atomically apply one approved and fresh retention review item. 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_review? +

Register the Mapi Agent Memory MCP server in PolicyLayer and add a rule for apply_memory_retention_review: 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_review? +

apply_memory_retention_review 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_review? +

Yes. Add a rate_limit block to the apply_memory_retention_review 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_review completely? +

Set action: deny in the PolicyLayer policy for apply_memory_retention_review. 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_review? +

apply_memory_retention_review 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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