maker_update_learner

THE RISK

Medium Risk

Why maker_update_learner needs a policy

This tool creates or modifies data reversibly by updating learner records. It does not delete data (ruling out Destructive), does not execute arbitrary code (ruling out Execute), involves no financial transactions (ruling out Financial), and is not merely a read operation.

From the tool's definition Tool name 'maker_update_learner' and description 'Update a learner' indicate a modification operation on learner data within the project management system. The verb 'update' is characteristic of Write-category operations.

Documented attack patterns abuse exactly the kind of access maker_update_learner gives an agent:

POLICY

How to control maker_update_learner

PolicyLayer is an MCP gateway — it sits between your AI agents and Crow, and nothing reaches the server without passing your rules. This is the rule we recommend for maker_update_learner:

policy.json

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

maker_update_learner 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.

Create a free account and register Crow — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

LIMIT THIS TOOL →

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EXPLORE

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Go deeper

The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Argument validation → Checking tool call arguments against schema and policy before they run.
Scoped token → Per-person credentials that grant a defined subset of servers and tools.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about maker_update_learner

What does the maker_update_learner tool do? +

Update a learner. It is categorised as a Write tool in the Crow MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on maker_update_learner? +

Register the Crow MCP server in PolicyLayer and add a rule for maker_update_learner: 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 Crow. Nothing to install.

What risk level is maker_update_learner? +

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

Can I rate-limit maker_update_learner? +

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

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

maker_update_learner is provided by the Crow MCP server (kh0pper/crow). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Crow tool call.

Start from Crow, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →