ofaudio-mcp

delete_voice

Delete a custom voice from ElevenLabs to free a slot. Requires confirmation, resolves names to IDs, and rejects ambiguous or premade voices.

Instructions

Delete a custom voice from the ElevenLabs account, freeing a voice slot.

DESTRUCTIVE and irreversible — you must pass confirm=True. Resolves a name to its id first and refuses if the name is ambiguous (pass the exact voice_id then). Premade voices can't be deleted. Also removes local nickname aliases and warns if a saved profile still pins the voice.

Args: voice: The voice name or id to delete. confirm: Must be True to actually delete.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "voice": "<voice>"
    },
    "name": "delete_voice"
  }
}

Input Schema

Name	Required	Description	Default
`voice`	Yes
`confirm`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 31, 2026

TDQS

A4.8/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description fully carries the transparency burden. It highlights destructive/irreversible nature, the confirm=True requirement, name-to-id resolution with ambiguity refusal, prohibition on premade voices, removal of local aliases, and profile-pinning warnings. This goes far beyond a basic delete operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core action, followed by critical warnings and a clear Args section. Every sentence adds value, from the destructive warning to the side-effect notifications, with no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity, absence of annotations, and lack of output schema, the description is remarkably complete. It covers safety, side effects, edge cases like ambiguous names and premade voices, and parameter semantics, giving an agent sufficient information to invoke correctly and anticipate consequences.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so description must compensate. It explains 'voice' as a name or ID, clarifies ambiguity behavior, and defines 'confirm' as a required safety flag. This adds essential meaning beyond the raw types in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the tool's purpose: deleting a custom voice from the ElevenLabs account, with the specific effect of freeing a voice slot. It clearly distinguishes from siblings like list_voices, get_voice, and clone_voice by focusing on deletion of custom voices only.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on when to use (deleting custom voices) and when not to (premade voices cannot be deleted), plus practical guidance around confirm=True and resolving ambiguous names. It does not explicitly name alternative sibling tools, but the exclusions and operational notes make usage context strong.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.