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@aiwerk/mcp-server-elevenlabs

@aiwerk/mcp-server-elevenlabs

by AIWerk
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

create_text_to_speech_generation

Convert text into spoken audio using a chosen voice and model, and deliver the generated speech to workspace webhooks.

Instructions

Create Speech Generation

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": "create_text_to_speech_generation"
  }
}

Input Schema

NameRequiredDescriptionDefault
textNoThe text to synthesize into speech.
voiceNoThe ID of the voice to speak with.
webhookNo
model_idNoThe model to use for the generation.
language_codeNo
output_formatNoThe audio encoding of the output, as `codec_sampleRateHz_bitrateKbps`. `mp3_44100_192` requires the Creator tier or above.
voice_settingsNoOverrides for the voice's saved settings, applied to one generation.
pronunciation_dictionary_locatorsNoPronunciation dictionaries to apply to the text, in order of precedence. Up to 3.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

D1.7/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false, so the safety/mutation profile is covered. The description adds nothing: it does not mention that this is an async generation job, whether a webhook result is required, credit/cost implications, or 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.

Conciseness2/5

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

Extremely short, but this is under-specification rather than conciseness; there is no structure or front-loaded detail to earn its brevity. The single phrase conveys no actionable information beyond the title.

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 an 8-parameter generation/creation tool with no output schema and no required-parameter guidance, the description is wholly inadequate. An agent cannot determine inputs, side effects, or result retrieval from it.

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

Parameters2/5

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

Eight parameters with 75% schema description coverage; the schema documents text, voice, output_format, and webhook reasonably well. The description contributes zero parameter meaning, leaving the lower-coverage fields (language_code, model_id, voice_settings, pronunciation_dictionary_locators) without any supplementary context.

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?

"Create Speech Generation" essentially restates the tool name (create_text_to_speech_generation) with no added specificity. It states a verb and resource but nothing about scope, output, or how it differs from the many sibling TTS tools (text_to_speech_full, text_to_speech_stream, text_to_dialogue, etc.).

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 when-to-use guidance, no exclusions, and no reference to any alternative despite a crowded sibling landscape of text-to-speech and speech-to-speech tools. An agent has no basis to prefer this tool over the others.

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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