Skip to main content
Glama

text_to_speech

Convert text to speech with YarnGPT. Pass text (required, max 2000 characters) and voice (required). response_format defaults to mp3 (mp3, wav, opus, or flac). Use list_voices to discover voices. API key comes from global_variables.

Input Schema

NameRequiredDescriptionDefault
textYesThe text to convert to speech. Max 2000 characters.
voiceYesVoice character to use. One of: Idera, Emma, Zainab, Osagie, Wura, Jude, Chinenye, Tayo, Regina, Femi, Adaora, Umar, Mary, Nonso, Remi, Adam. Default Idera if unsure; call list_voices for descriptions.
notification_messageNoShort user-facing sentence for this action if the follow-up reply fails. Plain text only; do not mention template syntax or variable names.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries the full disclosure burden. It usefully mentions the API key source, max text length, and default output format, but it does not describe what the tool returns, whether generation is synchronous, or any cost/rate-limit behavior.

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 compact and front-loads the core action and required inputs. The only wasted or confusing clause is the response_format mention, which refers to a parameter not present in the input schema.

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 simple generation tool with rich schema descriptions, the definition covers key operational details such as auth source and voice discovery. However, with no output schema, it leaves the return behavior unclear and includes a response_format detail that does not match the actual 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 100%, so the schema already defines all three parameters. The description repeats the text and voice requirements and adds some context, but it also mentions response_format even though that parameter is absent from the schema, while omitting notification_message.

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 states a specific verb and resource: convert text to speech using YarnGPT. It distinguishes the tool from its sibling by telling the agent to use list_voices for voice discovery, so the purpose is immediately clear.

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 explains required inputs, the character limit, default audio format, voice discovery via list_voices, and that the API key comes from global_variables. It gives clear usage context, though it does not specify when not to use this tool.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources