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ssm82

syntx-ai-mcp

by ssm82

generate-audio

Generate speech, voice-changed audio, or music from a text prompt. Provide a chat UUID and prompt, then retrieve the completed audio URL from the response.

Instructions

Generate audio (TTS, voice change, music) via syntx.ai. Mirrors syntx.audio.generate and the SPA ai-audio.sendMessage flow. Posts to POST /api/v1/audio/generate?ai_name={ai_name}. Requires a target chat UUID (use create-chat first). The result includes generation metadata returned by the API; follow up with wait-for-response or get-messages to read the completed audio URL once the model finishes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesText prompt describing the audio to produce.
ai_nameNoAudio provider name (e.g. "elevenlabs", "suno-music"). Use `list-models` with scope=audio to discover valid values.elevenlabs
durationNoTarget duration in seconds (music/clip models).
voice_idNoVoice identifier for TTS models (e.g. ElevenLabs voice_id).
chat_uuidYesTarget chat UUID (create one with create-chat).
file_urlsNoOptional input file URLs (e.g. source audio for voice-change). Mirrors the SPA `attachments` argument translated to `file_urls`.
model_typeNoModel identifier within the provider.
sample_rateNoSample rate override in Hz (e.g. 22050, 44100).
style_promptNoProvider-specific style/mood hint (e.g. "pop, sad, rainy night").
model_settingsNoProvider-specific settings merged into `body.settings` after the top-level fields above. Use for keys the top-level surface does not expose (e.g. suno wants `mode`, `is_instrumental`, `styles`, `title`, `negative_tags`, `source_clip_id`, `source_task_id`, `continue_at`). Merged AFTER the top-level fields, so values here override them. Only plain JSON values are allowed; arrays and nested objects are passed through verbatim.
Behavior5/5

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

With no annotations provided, the description carries the full burden and does so well. It discloses the HTTP endpoint, the prerequisite of a chat UUID, and the asynchronous nature of the result (generation metadata returned; audio URL available later via polling). This goes beyond what the schema alone conveys.

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 efficient and front-loaded with the core purpose, then adds contextual details about the endpoint, prerequisites, and follow-up. Every sentence contributes useful information, though the 'Mirrors...' sentence could be seen as minor redundancy for some users.

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 (10 parameters, nested objects) and lack of an output schema, the description covers the essential workflow: create chat, generate audio, then poll for the URL. It explains the result shape at a high level (metadata and URL) and clarifies dependencies (chat_uuid). This is appropriate, though it does not cover all edge cases or error handling.

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?

The input schema has 100% parameter coverage with detailed descriptions, so per the baseline the description need not compensate. While the description mentions the endpoint uses ai_name and that chat_uuid is required, it adds little beyond the schema's existing field explanations.

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 function with a specific verb and resource: 'Generate audio (TTS, voice change, music) via syntx.ai.' It also distinguishes from sibling tools like generate-image and generate-video by focusing on audio and listing audio-specific use cases.

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 provides concrete usage context: it requires a chat UUID created with create-chat first, and notes that follow-up with wait-for-response or get-messages is needed to retrieve the completed audio URL. It does not explicitly exclude alternatives, but the audio-specific purpose and prerequisite make its role clear.

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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