AI agents use deactivate_teacher 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.
Deactivating a teacher sets their status to inactive, which is a reversible state change (they can be reactivated, as evidenced by the sibling tool 'activate_teacher'). This is a Write operation modifying a record's status, not a destructive deletion.
From the tool's definition Mark teacher as inactive
Attacks that exploit this kind of access
Mark teacher as inactive. 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.
Register the Eduframe MCP server in PolicyLayer and add a rule for deactivate_teacher: 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.
deactivate_teacher is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the deactivate_teacher 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.
Set action: deny in the PolicyLayer policy for deactivate_teacher. 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.
deactivate_teacher 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.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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