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brandon-fryslie

elevenlabs-mcp

text_to_speech

Read-only

Convert text to natural-sounding speech using a selected voice, with options to adjust stability, similarity, style, speed, and output format. Saves the audio file to a specified directory.

Instructions

Convert text to speech with a given voice. Saves output file to directory (default: $HOME/Desktop).

Only one of voice_id or voice_name can be provided. If none are provided, the default voice will be used.

⚠️ COST WARNING: This tool makes an API call to ElevenLabs which may incur costs. Only use when explicitly requested by the user.

 Args:
    text (str): The text to convert to speech.
    voice_name (str, optional): The name of the voice to use.
    model_id (str, optional): The model ID to use for speech synthesis. Options include:
        - eleven_multilingual_v2: High quality multilingual model (29 languages)
        - eleven_flash_v2_5: Fastest model with ultra-low latency (32 languages)
        - eleven_turbo_v2_5: Balanced quality and speed (32 languages)
        - eleven_flash_v2: Fast English-only model
        - eleven_turbo_v2: Balanced English-only model
        - eleven_monolingual_v1: Legacy English model
        Defaults to eleven_multilingual_v2 or environment variable ELEVENLABS_MODEL_ID.
    stability (float, optional): Stability of the generated audio. Determines how stable the voice is and the randomness between each generation. Lower values introduce broader emotional range for the voice. Higher values can result in a monotonous voice with limited emotion. Range is 0 to 1.
    similarity_boost (float, optional): Similarity boost of the generated audio. Determines how closely the AI should adhere to the original voice when attempting to replicate it. Range is 0 to 1.
    style (float, optional): Style of the generated audio. Determines the style exaggeration of the voice. This setting attempts to amplify the style of the original speaker. It does consume additional computational resources and might increase latency if set to anything other than 0. Range is 0 to 1.
    use_speaker_boost (bool, optional): Use speaker boost of the generated audio. This setting boosts the similarity to the original speaker. Using this setting requires a slightly higher computational load, which in turn increases latency.
    speed (float, optional): Speed of the generated audio. Controls the speed of the generated speech. Values range from 0.7 to 1.2, with 1.0 being the default speed. Lower values create slower, more deliberate speech while higher values produce faster-paced speech. Extreme values can impact the quality of the generated speech. Range is 0.7 to 1.2.
    output_directory (str, optional): Directory where files should be saved (only used when saving files).
        Defaults to $HOME/Desktop if not provided.
    language: ISO 639-1 language code for the voice.
    output_format (str, optional): Output format of the generated audio. Formatted as codec_sample_rate_bitrate. So an mp3 with 22.05kHz sample rate at 32kbs is represented as mp3_22050_32. MP3 with 192kbps bitrate requires you to be subscribed to Creator tier or above. PCM with 44.1kHz sample rate requires you to be subscribed to Pro tier or above. Note that the μ-law format (sometimes written mu-law, often approximated as u-law) is commonly used for Twilio audio inputs.
        Defaults to "mp3_44100_128". Must be one of:
        mp3_22050_32
        mp3_44100_32
        mp3_44100_64
        mp3_44100_96
        mp3_44100_128
        mp3_44100_192
        pcm_8000
        pcm_16000
        pcm_22050
        pcm_24000
        pcm_44100
        ulaw_8000
        alaw_8000
        opus_48000_32
        opus_48000_64
        opus_48000_96
        opus_48000_128
        opus_48000_192

Returns:
    Text content with file path or MCP resource with audio data, depending on output mode.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
voice_nameNo
output_directoryNo
voice_idNo
stabilityNo
similarity_boostNo
styleNo
use_speaker_boostNo
speedNo
languageNoen
output_formatNomp3_44100_128
model_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior1/5

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

The annotation readOnlyHint: true contradicts the description, which states the tool makes API calls and saves files (write operations). Per scoring guidelines, description contradicts annotations, so score is 1. 'Annotation Contradiction' flag is true.

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 description is verbose and includes a full Python docstring format with Args and Returns sections. While well-structured and front-loaded with key constraints, it is longer than necessary and could be condensed by moving parameter details to the schema, which is empty.

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?

Given the tool's complexity (12 parameters) and the existence of an output schema, the description is quite complete. It covers purpose, usage constraints, parameter details, output variations, and a cost warning. However, it does not fully describe the return value format, lacking specifics about the MCP resource structure.

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?

Schema description coverage is 0%, so the description must compensate. It provides extensive explanations for most parameters: ranges for stability, speed, etc.; default values for model_id, output_format; and lists of valid options for model_id and output_format. This adds significant meaning beyond the bare schema, justifying a score of 4.

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 clearly states the tool's purpose: 'Convert text to speech with a given voice. Saves output file to directory.' It specifies the verb (convert), resource (text to speech), and side effect (file saving). This distinguishes it from sibling tools like speech_to_text or speech_to_speech.

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?

The description includes a constraint 'Only one of voice_id or voice_name can be provided' and a cost warning 'Only use when explicitly requested by the user.' However, it does not explicitly contrast with sibling tools like text_to_voice or speech_to_speech, so usage guidelines are clear but not exhaustive.

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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