VoiceHue text to speech

Create a multi-voice dialogue

create_dialogue

Speak a conversation with several voices and get ONE merged audio file (MP3 by default, or WAV). Each block has its own voice, text and optional language, speed, pitch, volume and pause after it. Up to 20 blocks on the free plan and 100 on pro, and 3,000 characters across all blocks per call. Each block is charged like a text_to_speech call with its voice. Use list_voices first to get voice ids.

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": {
      "blocks": "<blocks>"
    },
    "name": "create_dialogue"
  }
}

Input Schema

Name	Required	Description	Default
`blocks`	Yes	The lines of the dialogue, in order.
`format`	No	Audio format. MP3 is the default.	mp3

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 9, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Annotations only declare the mutation/safety profile (readOnlyHint=false, destructiveHint=false, openWorldHint=true, idempotentHint=false). The description goes well beyond them with quota behavior (20 blocks free / 100 pro), a 3,000-character cross-block cap, and the key cost model: "Each block is charged like a text_to_speech call with its voice." That billing and limit disclosure is exactly the context annotations cannot carry.

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?

Front-loaded with the outcome and output artifact first, then block composition, then hard limits, then cost, then the prerequisite. Five sentences, each carrying distinct operational information with no filler or repetition of the schema.

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?

With no output schema, the description correctly covers the return artifact (one merged MP3 by default, or WAV). It is complete on inputs, limits and cost, but doesn't say how the audio is delivered back (URL, base64, file handle), which is the remaining unknown an agent would want.

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 every block field (voice, text, language, speed, pitch, volume, pause_ms, speaker) and the format enum are already documented in the schema. The description only restates that each block has its own voice, text and optional tuning parameters, adding no syntax, defaults, or interaction rules beyond the structured fields; baseline 3 applies.

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?

"Speak a conversation with several voices and get ONE merged audio file" states a specific verb (speak/create speech) plus the distinctive resource outcome (a single merged multi-voice file). The emphasis on "ONE merged" and "several voices" implicitly separates it from the single-voice sibling text_to_speech without needing the sibling named.

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?

It gives an explicit prerequisite workflow ("Use list_voices first to get voice ids") and names the plan/character ceilings that determine when a call will succeed. What's missing is an explicit when-not or a direct contrast with text_to_speech for single-line cases, so routing between the two is inferred rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All VoiceHue text to speech tools Inspect

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