Delete an education entry by ID. Get the ID from get_profile.
AI agents call delete_education to permanently remove resources in Shortlist MCP Server — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
This tool permanently removes education records from the user's profile. While not financial or as critical as deleting an entire resume, deletion of profile data is irreversible and could impact job application history. The high severity reflects that a misused agent could erase legitimate educational credentials, requiring manual re-entry.
From the tool's definition Tool name is 'delete_education' with description 'Delete an education entry by ID.' The use of 'Delete' indicates irreversible removal of data.
Documented attack patterns abuse exactly the kind of access delete_education gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Shortlist MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for delete_education:
{
"version": "1",
"default": "deny",
"hide": [
"delete_education"
]
} delete_education disappears from the agent's tool list entirely, and any attempt to call it is denied. The rest of the server keeps working.
Free to start. No card required.
Delete an education entry by ID. Get the ID from get_profile. It is categorised as a Destructive tool in the Shortlist MCP Server MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Shortlist MCP Server MCP server in PolicyLayer and add a rule for delete_education: 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 Shortlist MCP Server. Nothing to install.
delete_education is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the delete_education 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 delete_education. 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.
delete_education is provided by the Shortlist MCP Server MCP server (mls-tech-inc/shortlistjobs-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Shortlist MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
32 Shortlist MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.