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AIWerk

@aiwerk/mcp-server-elevenlabs

by AIWerk

add_voice

Create a custom voice for speech synthesis by uploading audio recordings for voice cloning.

Instructions

Add Voice

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesThe name that identifies this voice. This will be displayed in the dropdown of the website.
labelsNoLabels for the voice. Keys can be language, accent, gender, or age.
descriptionNoA description of the voice.
files_pathsNoA list of file paths to audio recordings intended for voice cloning. Local paths. Required for this call.
files_filenamesNoFilenames to send for "files". Some endpoints infer the audio format from them.
files_base64_listNoBase64 contents for "files", one entry per file. Use this when the server cannot read your local disk.
remove_background_noiseNoIf set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

D1.7/5.0
Behavior1/5

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

Annotations already declare readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false, but the description adds zero context: no mention that voice cloning consumes uploaded audio, that training may be asynchronous, or that repeated calls create duplicates (non-idempotent). It contributes nothing beyond the structured data.

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

Conciseness2/5

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

At two words it is technically short, but this is under-specification rather than conciseness; there is no front-loaded explanation of purpose, scope, or arguments. Nothing earns or fails to earn a place because nothing is there.

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

Completeness1/5

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

For a 7-parameter, non-idempotent mutation tool with no output schema, the definition is completely inadequate. It omits the cloning workflow, the required-vs-optional file input patterns, and any distinction from the many sibling voice tools.

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

Parameters3/5

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

Schema description coverage is 100% across all 7 parameters, so the schema itself documents name, labels, description, file paths/filenames/base64 lists, and background-noise removal. Baseline is 3 when the schema does the heavy lifting, and the description adds no additional parameter meaning.

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

Purpose2/5

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

The entire description is "Add Voice", which merely restates the tool name and the annotation title. It gives no verb-plus-resource specificity beyond the name itself and does nothing to distinguish this tool from siblings such as create_voice, edit_voice, delete_voice, or add_sharing_voice.

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

Usage Guidelines1/5

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

There is no guidance whatsoever about when to use this tool versus create_voice/add_sharing_voice/add_pvc_voice_samples, nor any stated prerequisites. The agent is left to infer everything from the name alone.

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

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