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AIWerk

@aiwerk/mcp-server-elevenlabs

by AIWerk

get_pvc_sample_audio

Read-onlyIdempotent

Fetch audio for a specific voice sample by voice and sample IDs, with optional background-noise removal for cleaner playback.

Instructions

Retrieve Voice Sample Audio

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
voice_idYesVoice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices.
sample_idYesSample ID to be used
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

C2.5/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds no behavioral context beyond that, such as whether it requires authentication, returns a URL or binary, or has rate limits.

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

Conciseness3/5

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

The four-word phrase is concise and front-loaded, but it is under-specified for a tool with three parameters and no output schema. It earns no place beyond repeating the title, so it is too minimal for the tool's complexity.

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

Completeness2/5

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

No output schema exists, and the description does not explain what the returned audio is, its format, or how it relates to sibling tools. Annotations and schema cover safety and parameters, but the description leaves the agent without enough context to know when this tool is the right choice.

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%, so the schema fully documents all three parameters including voice_id, sample_id, and remove_background_noise. The description adds no parameter meaning beyond what the schema provides; baseline 3 applies.

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

Purpose3/5

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

States a verb (Retrieve) and resource (Voice Sample Audio), but essentially restates the tool name with no additional detail or sibling differentiation. An agent cannot distinguish it from get_audio_from_sample or get_pvc_sample_visual_waveform based on this description.

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

Usage Guidelines2/5

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

No when-to-use guidance or alternatives are provided. The description does not mention when to choose this tool over get_audio_from_sample or any other audio retrieval sibling.

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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