This record as markdown: /tools/synthetic-ai-ae-mcp/remove-effect.md
What remove_effect does on Ae
AI agents call remove_effect to permanently remove resources in Ae, typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
| Parameter | Type | Required | Description |
|---|---|---|---|
save | boolean | — | |
compName | string | Yes | |
layerName | string | Yes | |
timeoutMs | number | — | |
effectName | string | — | Effect display name or match name. |
effectIndex | number | — | 1-based effect index. |
projectPath | string | — |
Parameters from the server's own tool schema.
Why remove_effect is rated Critical
An AI agent that decides to call remove_effect doesn't hesitate, doesn't double-check, and doesn't stop at one. Whatever it removes from Ae is gone. There is no undo for destructive operations.
Attacks that exploit this kind of access
The rule that runs remove_effect safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Ae, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For remove_effect, this is the rule to start with:
remove_effect is removed from the agent's tool list entirely, so the agent never calls it. The rest of the server keeps working.
The button opens the PolicyLayer dashboard: create your workspace, connect Ae, apply this rule, and every remove_effect call is checked against it from then on.
Questions about remove_effect
Remove an effect from a layer by name, match name, or index. It is categorised as a Destructive tool in the Ae MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
remove_effect accepts 7 parameters: save, compName, layerName, timeoutMs, effectName, effectIndex, projectPath. Required: compName, layerName. The full parameter table on this page comes from the server's own tool schema.
Register the Ae MCP server in PolicyLayer and add a rule for remove_effect: 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 Ae. Nothing to install.
remove_effect 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_effect 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_effect. 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_effect is provided by the Ae MCP server (@synthetic-ai/ae-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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