Delete a node from Figma
AI agents call delete_node to permanently remove resources in MCP Figma — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Deleting a node in Figma is an irreversible operation that removes design elements permanently. This cannot be undone programmatically through the MCP interface and represents destruction of user-created design work.
From the tool's definition Tool name is 'delete_node' with description 'Delete a node from Figma'. The server description also mentions 'delete_multiple_nodes' as a sibling tool, confirming deletion capability.
Attacks that exploit this kind of access
Delete a node from Figma. It is categorised as a Destructive tool in the MCP Figma MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the MCP Figma MCP server in PolicyLayer and add a rule for delete_node: 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 MCP Figma. Nothing to install.
delete_node 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_node 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_node. 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_node is provided by the MCP Figma MCP server (yelowflash09/figma_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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