Delete an optimization. Args: optimization_id: ID of the optimization to delete Returns: Dictionary containing deletion result
AI agents call delete_optimization to permanently remove resources in QuantConnect 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 an optimization configuration and its associated data from the QuantConnect platform. In the context of a trading platform, deleting an optimization cannot be undone and represents loss of research work, backtesting results, and strategy configurations.
From the tool's definition Tool name is 'delete_optimization' with description 'Delete an optimization.' The verb 'delete' combined with the permanent removal of an optimization object indicates irreversible destruction of data.
Documented attack patterns abuse exactly the kind of access delete_optimization gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and QuantConnect MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for delete_optimization:
{
"version": "1",
"default": "deny",
"hide": [
"delete_optimization"
]
}delete_optimization 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 optimization. Args: optimization_id: ID of the optimization to delete Returns: Dictionary containing deletion result. It is categorised as a Destructive tool in the QuantConnect MCP Server MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the QuantConnect MCP Server MCP server in PolicyLayer and add a rule for delete_optimization: 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 QuantConnect MCP Server. Nothing to install.
delete_optimization 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_optimization 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_optimization. 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_optimization is provided by the QuantConnect MCP Server MCP server (taylorwilsdon/quantconnect-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 50 QuantConnect MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
50 QuantConnect MCP Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.