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brandon-fryslie

elevenlabs-mcp

speech_to_text

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Transcribe speech from audio files using ElevenLabs API. Supports automatic language detection, speaker diarization, and flexible output options including file saving or direct text return.

Instructions

Transcribe speech from an audio file. When save_transcript_to_file=True: Saves output file to directory (default: $HOME/Desktop). When return_transcript_to_client_directly=True, always returns text directly regardless of output mode.

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

Args:
    file_path: Path to the audio file to transcribe
    language_code: ISO 639-3 language code for transcription. If not provided, the language will be detected automatically.
    diarize: Whether to diarize the audio file. If True, which speaker is currently speaking will be annotated in the transcription.
    save_transcript_to_file: Whether to save the transcript to a file.
    return_transcript_to_client_directly: Whether to return the transcript to the client directly.
    output_directory: Directory where files should be saved (only used when saving files).
        Defaults to $HOME/Desktop if not provided.

Returns:
    TextContent containing the transcription or MCP resource with transcript data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
input_file_pathYes
language_codeNo
diarizeNo
save_transcript_to_fileNo
return_transcript_to_client_directlyNo
output_directoryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior1/5

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

The description reveals that the tool saves files and makes API calls, contradicting the readOnlyHint annotation (which implies no modification). This is a clear annotation contradiction, earning the lowest score.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

The description is well-structured, starting with the main purpose, then flag behaviors, cost warning, and parameter definitions. Slightly verbose but clear and front-loaded.

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

Completeness3/5

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

Given the presence of an output schema and 6 parameters, the description covers basic usage but omits details like supported audio formats, file size limits, and language code constraints. The parameter mismatch also detracts from completeness.

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?

Despite 0% schema description coverage, the description explains each parameter's purpose. However, there is a parameter name mismatch (description uses 'file_path', schema uses 'input_file_path'), causing confusion and reducing reliability.

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 'Transcribe speech from an audio file', providing a specific verb-resource pair. It distinguishes from sibling tools like speech_to_speech or text_to_speech by focusing on transcription.

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 includes a cost warning and advises only using when explicitly requested by the user, offering some guidance. However, it does not specify when to use this tool over alternatives (e.g., speech_to_speech) or provide exclusion criteria.

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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