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ElevenLabs Voice-to-Voice Agent

ElevenLabs Voice-to-Voice Agent

by Begwen
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

list_voices

List all ElevenLabs voices, including IDs, names, and labels, to identify available options for your voice-to-voice AI conversations.

Instructions

List all voices available in ElevenLabs. Returns voice IDs, names, and labels.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_voices"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns voice IDs, names, and labels, which gives useful output expectations, but it does not mention authentication, pagination, or any side effects. For a simple read-only list, this is adequate but lacks depth.

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 a single sentence that front-loads the verb and outcome, with no redundant words or filler. It is appropriately brief for such a simple tool.

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

Completeness4/5

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

The description covers the tool's core function and return fields, making it sufficient for a parameterless list operation. The lack of an output schema is mitigated by explicitly stating the returned data types.

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

Parameters4/5

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

The tool has zero parameters, so there is nothing for the description to explain. The schema is trivially 100% covered, and the baseline for zero-parameter tools is 4, which applies here.

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 uses the specific verb 'List' and identifies the resource as 'voices available in ElevenLabs', making it clear this is a listing operation. This distinguishes it from 'get_voice' (retrieving a single voice) and 'list_models' (listing models).

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

Usage Guidelines3/5

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

The description implies this tool is for fetching all voices, but it does not explicitly mention alternatives or when not to use it. Sibling tool names like 'get_voice' suggest a contrast, but the description does not articulate this; guidance is only implied.

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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