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Venice MCP Server

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by veniceai

Venice TTS (Speech)

venice_tts

Convert text to speech with cloned voices and emotion tags. Supports wallet authentication without a Venice account.

Instructions

Convert text to speech. Supports cloned voices + emotion tags ([whispers], [sarcastically], etc.). Supports x402 wallet auth (no Venice account needed) and API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesText to convert to speech (max 4096 chars).
modelNo
speedNo
voiceNoVoice id; see venice://voices.
response_formatNo
Behavior2/5

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

With no annotations provided, the description carries the full burden. It mentions authentication methods but does not disclose behavioral traits such as output format, error handling, rate limits, or whether the operation is destructive. The description lacks crucial context beyond basic functionality.

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?

The description consists of two short sentences, conveying essential information without any redundant or irrelevant content. Every word serves a purpose, making it highly efficient for an agent to parse quickly.

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?

Given the tool has 5 parameters (1 required), no annotations, and no output schema, the description is insufficient. It does not explain return values, behavior of unseen parameters, or how emotion tags integrate with the input. The presence of many sibling tools demands more context to differentiate, but the description is too minimal.

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 only 40% (input and voice have descriptions). The description adds value by mentioning cloned voices and emotion tags, which relate to the input and voice parameters. However, it provides no additional meaning for the model, speed, and response_format parameters, which lack schema descriptions. It partially compensates but is not comprehensive.

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 'Convert text to speech', specifying the action and resource. It distinguishes from sibling tools like venice_asr (speech recognition) and venice_music_generate by mentioning cloned voices and emotion tags, which are unique features.

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 is provided on when to use this tool versus alternatives like venice_asr for speech recognition or venice_chat for conversation. There are no explicit when-to-use or when-not-to-use instructions, leaving the agent without comparative context.

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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