AI agents call remove_component to permanently remove resources in PyPSA MCP — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Removing a component from an energy system model is an irreversible operation that destroys data and cannot be undone by simple reversal. While the impact is scoped to a single model component rather than an entire model, it still meets the Destructive category criterion of 'irreversibly deletes or overwrites data.' The high severity reflects that an AI agent could accidentally corrupt a complex energy system model…
From the tool's definition Tool name is 'remove_component' with description 'Remove a component from a model.' The verb 'remove' indicates deletion. Combined with sibling tools like 'delete_model', this server's pattern confirms irreversible data removal.
Documented attack patterns abuse exactly the kind of access remove_component gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and PyPSA MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for remove_component:
{
"version": "1",
"default": "deny",
"hide": [
"remove_component"
]
}remove_component disappears from the agent's tool list entirely, and any attempt to call it is denied. The rest of the server keeps working.
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Remove a component from a model. It is categorised as a Destructive tool in the PyPSA MCP MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the PyPSA MCP server in PolicyLayer and add a rule for remove_component: 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 PyPSA MCP. Nothing to install.
remove_component 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 remove_component 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 remove_component. 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.
remove_component is provided by the PyPSA MCP server (open-energy-transition/pypsa-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 22 PyPSA MCP tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
22 PyPSA MCP tools catalogued and risk-classified — across an index of 42,500+ MCP servers.