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List resources

list_resources
Read-onlyIdempotent

Fetch voice IDs and names for ElevenLabs, Kling, or Veo to pass the correct voice ID to audio or video generation tools.

Instructions

List a model provider's voices so you can pass the right id to a generation tool. Default 'elevenlabs-voices' (the voices for generate_audio); also covers Kling and Google Veo voices. Returns each voice's id and name. (This is UnificAlly's resource catalog; it is not the MCP protocol's resources/list.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax items to return. Default 50.
queryNoFilter the voice list by name/labels — space-separated words, all must match (e.g. 'british female'). Applies to all voice lists.
categoryNoElevenLabs voices only: which set to return. Default 'premade' (~21 stable official voices); 'all' includes the large shared library.
resourceNoWhich provider's voice list to return. Default 'elevenlabs-voices'. Options: 'elevenlabs-voices' (ElevenLabs TTS/dialogue/voice-changer voices — use the voice_id in generate_audio), 'kling-voices' (Kling video voices — use the id as voice_id), 'veo-voices' (Google Veo voices — use the id as 'voice'; requires an image/character reference). Aliases 'tts'/'kling'/'veo' work. NOTE: this is UnificAlly's provider-resource catalog, distinct from the MCP protocol's resources/list.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower, yet the description adds genuinely useful behavior: what the response contains ('each voice's id and name'), per-provider defaults, and the aliases. The Veo prerequisite (image/character reference) is a real constraint not visible in annotations.

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?

Three tight sentences, front-loaded with the primary purpose and the default resource, followed by what is returned and the disambiguation note. No filler and no repetition of schema details.

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?

With no output schema, the description supplies the return shape (id and name), the default and alias options, and the disambiguation from MCP resources/list. For a zero-required-parameter read tool, an agent has everything needed to call it correctly.

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 all four parameters (limit, query, category, resource) are already documented in detail in the schema. The description reinforces the default resource and the id-vs-voice key difference, but adds little syntax or semantics beyond what the schema already provides.

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?

Opens with a specific verb+resource ('List a model provider's voices') and states the downstream purpose (passing the right id to a generation tool). It explicitly distinguishes itself from the MCP protocol's resources/list and, implicitly, from list_models by scoping to provider voice catalogs.

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?

Gives clear usage context: default resource 'elevenlabs-voices' feeds generate_audio, while Kling and Veo lists serve video generation, and it notes Veo voices require an image/character reference. It stops short of explicitly naming sibling tools like generate_video as the consumer or stating when not to call it.

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