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AIWerk

@aiwerk/mcp-server-elevenlabs

by AIWerk

get_library_voices

Read-onlyIdempotent

Retrieve and filter available voices from the ElevenLabs library by language, gender, accent, category, and more. Sort results by creation date, usage, or popularity to find the right voice for your project.

Instructions

Get Voices

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ageNoAge used for filtering
pageNo
sortNoSort criteria. Must be one of: created_date, usage_character_count_1y, trending, cloned_by_count.
accentNoAccent used for filtering
genderNoGender used for filtering
localeNoLocale used for filtering
searchNoSearch term used for filtering
categoryNoVoice category used for filtering
featuredNoFilter featured voices
languageNoLanguage used for filtering
owner_idNoFilter voices by public owner ID
page_sizeNoHow many shared voices to return at maximum. Can not exceed 100, defaults to 30.
use_casesNoUse-case used for filtering
descriptivesNoSearch term used for filtering
reader_app_enabledNoFilter voices that are enabled for the reader app
include_custom_ratesNoInclude/exclude voices with custom rates
include_live_moderatedNoInclude/exclude voices that are live moderated
min_notice_period_daysNoFilter voices with a minimum notice period of the given number of days.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2/5.0
Behavior2/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is covered. The description adds nothing beyond that — no indication of pagination behavior, result ordering, or that these are shared/library voices.

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?

It is short only because it is under-specified, not because it is efficient. A two-word fragment carries no useful information.

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?

For an 18-parameter listing tool with no output schema, the definition should clarify what resource is being listed, that results are paginated (page/page_size exist), and how it differs from sibling voice endpoints. The read-only annotations cover safety but not this scope, leaving the definition substantially incomplete.

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 94%, so the 18 parameters are already well documented by the schema itself. The description contributes no additional clarification, but the high coverage establishes the baseline of 3.

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 description 'Get Voices' merely restates the tool name with no verb-level specificity about scope, source, or filtering. It does not distinguish this tool from close siblings such as get_voices, get_user_voices_v2, get_similar_library_voices, or get_voice_by_id.

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?

No guidance whatsoever on when to use this tool versus the many other voice-retrieval siblings. An agent has nothing to route on beyond the name.

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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