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suprsonic-mcp

suprsonic-mcp

by O-mega-Enterprise
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

tts

Convert text into speech audio with provider and voice model options, supporting up to 2,000 characters per request for 2 credits.

Instructions

Convert text to speech audio. Cost: 2 credits.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "text": "<text>"
    },
    "name": "tts"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYesText to convert (max 2000 chars).
providerNoTTS provider.auto
voice_modelNoDeepgram voice model ID.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv0.3.1
    • addedInput schema / properties / provider
      Added value: +{
+  "default": "auto",
+  "description": "TTS provider.",
+  "enum": [
+    "auto",
+    "deepgram",
+    "elevenlabs"
+  ],
+  "type": "string"
+}
    • changedInput schema / properties / text / description
      Previous value: -"Text to convert to speech"New value: +"Text to convert (max 2000 chars)."
    • removedInput schema / properties / voice_description
      Removed value: -{
-  "description": "Describe the voice, e.g. 'calm professional female'",
-  "type": "string"
-}
    • addedInput schema / properties / voice_model
      Added value: +{
+  "description": "Deepgram voice model ID.",
+  "type": "string"
+}
  2. First observedv0.3.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose one genuinely useful non-schema trait: the 2-credit cost. It says nothing about the return format (URL vs. binary), latency, provider fallback behavior when 'auto' is used, or async handling, which are real gaps for an audio-generation tool.

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

Conciseness5/5

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

Two short sentences with zero filler, and the core action is front-loaded ahead of the cost note. Nothing to trim.

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?

For a 3-parameter generation tool with no annotations and no output schema, the description covers the action and cost but leaves the return contract and provider-selection behavior unexplained. Adequate but incomplete.

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 100%, so the schema already documents 'text', the provider enum, and 'voice_model'. The description adds no parameter-level meaning, so the baseline of 3 applies.

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?

States a concrete verb+resource ('Convert text to speech audio'), which is immediately distinguishable from the sibling 'stt' (the inverse direction). It does not, however, differentiate itself from 'sound-generate' or 'transcribe', so sibling routing still requires inference.

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?

There is no guidance on when to use this versus the related audio siblings ('stt', 'sound-generate', 'transcribe'), nor any stated prerequisites. The agent is left to infer that this is the text-in/audio-out path from the name alone.

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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