update_planned_course · Eduframe MCP: Risk & Policy

WHAT IT DOES

What update_planned_course does on Eduframe

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

WHY IT NEEDS A POLICY

Why update_planned_course needs a policy

This tool modifies existing data (a planned course) in a reversible manner. It is not a read operation (retrieves data), not destructive (no deletion/purging), not an execute operation triggering external code, and not financial. The severity is medium because misuse by an AI agent could alter course schedules affecting students and operations, but the impact is limited to a single entity and reversible.

From the tool's definition Tool name 'update_planned_course' and description 'Update a planned course' indicate data modification. The action is reversible (changes can be corrected), distinguishing it from destructive operations.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

update_planned_course Rate-limited

update_planned_course 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": {
    "update_planned_course": {
      "limits": [
        {
          "counter": "update_planned_course_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Eduframe, so you can run agents against it safely.

FAQ

Questions about update_planned_course

What does the update_planned_course tool do? +

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

How do I enforce a policy on update_planned_course? +

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

What risk level is update_planned_course? +

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

Can I rate-limit update_planned_course? +

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

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

update_planned_course is provided by the Eduframe MCP server (martijnpieters/eduframe-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.