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@aiwerk/mcp-server-elevenlabs

by AIWerk
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TypeScript
Hybrid

stream_compose

Generate and stream composed music from prompts or composition plans, returning audio bytes that can be saved to a specified output path. Spends ElevenLabs credits.

Instructions

Stream Composed Music Spends ElevenLabs credits. Returns audio/* bytes; pass output_path to save them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNo
promptNo
model_idNo
finetune_idNo
lyrics_textNo
output_pathNoWhere to write the returned bytes. Relative paths resolve against ELEVENLABS_OUTPUT_DIR. Omit it to get the data inline as base64 (small files only).
music_promptNoComposition plan for the `music_v1` model. Using this field with any other model will result in an error.
output_formatNoOutput format of the generated audio. Formatted as codec_sample_rate_bitrate. Use "auto" (the default) to let the API pick the best format for the selected model: mp3_44100_128 for v1 models and mp3_48000_192 for v2 models.
generation_modeNo
music_length_msNo
composition_planNo
finetune_strengthNoHow strongly the finetune influences the generation. Defaults to 1.0 (full strength). Lower values soften the influence of the finetune, leaving more room for prompt-level steering. Only meaningful when `finetune_id` is also provided.
force_instrumentalNoIf true, guarantees that the generated song will be instrumental. If false, the song may or may not be instrumental depending on the `prompt`. Can only be used with `prompt`.
use_phonetic_namesNoIf true, proper names in the prompt will be phonetically spelled in the lyrics for better pronunciation by the music model. The original names will be restored in word timestamps.
store_for_inpaintingNoWhether to store the generated song for inpainting.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

Annotations state readOnlyHint=false, idempotentHint=false, openWorldHint=true, destructiveHint=false. The description adds two useful behavioral facts: it consumes ElevenLabs credits and returns audio/* bytes, with output_path controlling inline vs. saved. That covers cost and return channel, but not auth, errors, streaming semantics, 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.

Conciseness4/5

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

Two sentences, front-loaded, no filler. It is slightly terse given a 15-parameter schema, but every sentence earns its place and there is no structural waste.

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

Completeness2/5

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

For a 15-parameter, zero-required, streaming generation tool with no output schema and 47% schema coverage, the description is far too thin. It omits prompt/lyrics/model relationships, generation_mode meaning, music_length_ms, seed, finetune interactions, and the music_v1-only constraint on music_prompt/composition_plan already noted in schema.

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 47%, so the schema explains some parameters (output_path, output_format, finetune_strength, force_instrumental, use_phonetic_names, store_for_inpainting, music_prompt) while several remain bare (seed, prompt, model_id, finetune_id, lyrics_text, generation_mode, music_length_ms, composition_plan). The description adds output_path semantics but does not compensate for the undocumented half.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: it composes music by streaming. 'Stream Composed Music' names the operation and the artifact clearly, distinguishing it from text-to-speech or sound_generation siblings. It falls short of a 5 only because it doesn't discuss ties to sibling compose tools.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus siblings like compose_detailed, compose_detailed_stream, compose_plan, or sound_generation. The only routing hint is the output_path behavior, which is operational rather than selection guidance.

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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