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callremind

CallRemind MCP Server

Official
by callremind

kokoroPreview

Generate a short voice clip with Kokoro TTS and receive the audio to preview voice options. Use it to compare available voices and choose the right one for your calls.

Instructions

Generate a short voice clip using the Kokoro TTS engine and return the audio (raw or WAV depending on the call). Use to pick a voice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesText to synthesize
speedNoSpeaking speed factor (default 1)
voiceNoKokoro voice id from listVoices, e.g. af_heart / am_adam. Defaults to af_heart.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.6

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description must carry the behavioral disclosure burden. It discloses that the tool returns audio in raw or WAV form and that clips are short, which is useful. However, 'depending on the call' is ambiguous, and there is no mention of side effects, rate limits, or prerequisites.

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 short and front-loaded, stating the main behavior in the first sentence. The second sentence provides a clear use case. Slight ambiguity in 'depending on the call' keeps it from being fully polished.

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?

The description is adequate for a small preview tool, but the output format ambiguity ('raw or WAV depending on the call') is not resolved, and with no output schema or annotations, an agent may not know exactly what to expect or how to control the format.

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?

Input schema covers 100% of parameters with clear descriptions, so the baseline is 3. The tool description adds no extra parameter-level meaning beyond what the schema already provides.

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: generate a short voice clip with the Kokoro TTS engine and return audio. It clearly conveys the tool's core purpose. However, it does not explicitly differentiate from sibling tools like previewEdgeVoice or generateTts, leaving some selection ambiguity.

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 phrase 'Use to pick a voice' gives a clear intended usage context: previewing voices before selection. It does not mention alternatives or exclusions, but the guidance is explicit enough for a preview tool.

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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