memory_recall_feedback

A write tool on the Agent-Memory-OS MCP server.

SERVERAgent-Memory-OS SOURCEyamantaka520/Agent-Memory-OS

Medium RISK CLASS

Category Write

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade B, identity unverified Pull the record →

This record as markdown: /tools/agent-memory-os/memory-recall-feedback.md

WHAT IT DOES

What memory_recall_feedback does on Agent-Memory-OS

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

RISK

Why memory_recall_feedback is rated Medium

The tool operates on a local SQLite memory store. While the description is empty (reducing confidence), the name pattern and server context indicate this writes feedback annotations to the memory system, making it a Write operation. It is not Read (feedback modifies state), not Destructive (feedback is reversible), not Execute/Financial/Other.

From the tool's definition Tool name 'memory_recall_feedback' suggests feedback is being recorded against recalled memories. In the context of a memory engine with 'memory_add', 'memory_consolidate', and 'memory_link' sibling tools, this likely modifies stored memory state by…

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs memory_recall_feedback safely

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

memory_recall_feedback Rate-limited

memory_recall_feedback 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": {
    "memory_recall_feedback": {
      "limits": [
        {
          "counter": "memory_recall_feedback_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 Agent-Memory-OS, apply this rule, and every memory_recall_feedback call is checked against it from then on.

FAQ

Questions about memory_recall_feedback

What does the memory_recall_feedback tool do? +

memory_recall_feedback is a write tool on the Agent-Memory-OS MCP server. It is categorised as a Write tool in the Agent-Memory-OS MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on memory_recall_feedback? +

Register the Agent-Memory-OS MCP server in PolicyLayer and add a rule for memory_recall_feedback: 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 Agent-Memory-OS. Nothing to install.

What risk level is memory_recall_feedback? +

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

Can I rate-limit memory_recall_feedback? +

Yes. Add a rate_limit block to the memory_recall_feedback 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 memory_recall_feedback completely? +

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

memory_recall_feedback is provided by the Agent-Memory-OS MCP server (yamantaka520/Agent-Memory-OS). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

KEEP EXPLORING

More on Agent-Memory-OS, and thousands of servers like it.

This server

All 12 Agent-Memory-OS tools →

Across the catalogue

team_manager_write_memory on Team Manager MCP → The MCP Attack Database →

Guides

Govern customer-ops agents →Argument validation →Scoped token →