AI agents use effect_repeat to create or update resources in AudacityMCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your AudacityMCP environment.
This tool creates or modifies audio data in a reversible manner (the user can undo the repeat operation in Audacity). It does not delete data irreversibly, nor does it execute arbitrary commands or move money. While it changes the audio project, the change is non-destructive and can be undone, fitting the Write category.
From the tool's definition Tool name 'effect_repeat' and description 'Repeat the selected audio a number of times' indicates the tool modifies audio by duplicating/repeating a segment, creating new audio data within the project.
Documented attack patterns abuse exactly the kind of access effect_repeat gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and AudacityMCP, and nothing reaches the server without passing your rules. This is the rule we recommend for effect_repeat:
{
"version": "1",
"default": "deny",
"tools": {
"effect_repeat": {
"limits": [
{
"counter": "effect_repeat_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}effect_repeat stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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Repeat the selected audio a number of times. It is categorised as a Write tool in the AudacityMCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Audacity MCP server in PolicyLayer and add a rule for effect_repeat: 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 AudacityMCP. Nothing to install.
effect_repeat is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the effect_repeat 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 effect_repeat. 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.
effect_repeat is provided by the Audacity MCP server (xdarkzx/audacity-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 131 AudacityMCP tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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131 AudacityMCP tools catalogued and risk-classified — across an index of 42,500+ MCP servers.