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speak-to-me-mcp

configure_speech

Set default text-to-speech preferences for the current session, including engine, voice, rate, OpenAI model, and speaking style. Run without arguments to view current settings.

Instructions

Set default speech preferences for this session. Changes persist until the MCP server restarts. Call with no arguments to view current config.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rateNoSpeech rate in words per minute for system engine. Default 200. Range: 50-500.
voiceNoDefault system voice name (e.g. 'Samantha', 'Daniel', 'Shelley').
engineNoDefault TTS engine: "system" or "openai".
openai_modelNoOpenAI model: "tts-1" (fast) or "tts-1-hd" (higher quality).
openai_voiceNoDefault OpenAI voice (e.g. 'nova', 'alloy', 'onyx').
speech_styleNoSpeaking style or persona that shapes how text is composed (e.g. 'talk like a clown', 'be super concise', 'speak like a business woman'). Set to empty string to clear.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations present, the description carries the full burden and does disclose an important behavioral trait: changes are session-scoped and 'persist until the MCP server restarts'. That volatility disclosure plus the no-arg read mode is meaningful. It still omits what happens to in-flight or subsequent speech and how invalid values are handled, so it is strong but not exhaustive.

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?

Three short sentences, front-loaded with the core action, followed by the persistence caveat and the read-only invocation mode. Every sentence earns its place with no filler.

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?

For a six-parameter, all-optional configuration tool with no output schema, the description covers scope, lifetime and the zero-argument read behavior, which is what an agent needs to call it safely. It is slightly incomplete on the relationship to the 'speech_style' sibling tool and on interaction with active speech.

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% and every one of the six parameters (rate, voice, engine, openai_model, openai_voice, speech_style) is documented in the schema with defaults, ranges and examples. The description adds no parameter-level detail beyond the schema, so the baseline 3 is correct.

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?

The description states a specific verb and resource ('Set default speech preferences') with a clear scope ('for this session'), so an agent knows exactly what the tool mutates. It does not, however, distinguish itself from the sibling 'speech_style' tool or explain how a 'default preference' differs from a per-call style, leaving some ambiguity among siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives one concrete usage rule ('Call with no arguments to view current config'), which is genuinely useful dual-mode guidance. But it offers no when-not guidance and never routes the agent away from the closely named sibling 'speech_style', so selection between the two remains implied rather than stated.

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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