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neuroverse

neuroverse

by joshua400
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Synthesize Speech

neuroverse_synthesize

Convert text into spoken audio using Coqui TTS. Supports language selection and returns the path to the generated audio file.

Instructions

Synthesize text to speech using Coqui TTS.

Args:

  • text (string): Text to synthesize

  • language (string): Language code

Returns: JSON with the path to the generated audio file

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": {
      "text": "<text>"
    },
    "name": "neuroverse_synthesize"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYesText to synthesize into speech
languageNoLanguage code (e.g. en, ta, hi)en

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior3/5

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

Annotations provide readOnlyHint=false, openWorldHint=true, which hint at mutation and external dependencies. The description adds that it uses Coqui TTS and returns a file path, but does not detail latency, file format, or potential side effects.

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 concise and well-organized with a clear one-line action, parameter list, and return description. However, it could be slightly more efficient by merging the parameter list into prose.

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?

Given the simple tool (2 params, no output schema), annotations present, the description adequately covers purpose, parameters, and return. It misses limitations like max text length or supported languages beyond examples, but is mostly complete.

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 has 100% coverage of parameters with descriptions. The description repeats the schema info without adding new meaning, so 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?

The description clearly states the tool synthesizes text to speech using Coqui TTS, specifying the verb and resource. It distinguishes from siblings like neuroverse_transcribe (speech-to-text) and neuroverse_process (generic).

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 on when to use this tool versus alternatives like neuroverse_execute or neuroverse_process. No context about prerequisites or when not to use it.

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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