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TonePerfect MCP server

TonePerfect MCP server

by toneperfect
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TypeScript
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List supported languages

list_languages
Read-onlyIdempotent

Fetch supported languages, scored dimensions, and limits for TonePerfect pronunciation assessment so you can confirm API capabilities before assessing audio; no API key required.

Instructions

List the languages, scored dimensions and limits of the TonePerfect pronunciation assessment API (GET /v1/capabilities). Free, no API key needed.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_languages"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already establish that this is a safe, read-only, idempotent operation. The description adds meaningful behavioral context beyond them by disclosing the exact GET endpoint and that access is free with no API key required, though it does not describe the response format.

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 is a single tightly written sentence that front-loads the primary purpose and packs in the endpoint, cost, and authentication details without any filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no parameters, no output schema, and annotations that already cover its safety profile, the description provides everything needed to call it correctly: what it returns, the endpoint, and the access requirements. Nothing material is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes no parameters, so there are no parameter semantics to explain and the baseline score of 4 applies. The description does not need to compensate for any schema gaps.

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 uses a specific verb ("List") and names the exact resources returned: languages, scored dimensions, and limits. It also identifies the API endpoint, making the tool's purpose unambiguous and clearly distinct from the sibling assessment and explanation tools.

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 conveys useful context that the tool is free and requires no API key, but it does not explicitly state when to use this tool versus the sibling tools or what prerequisites or follow-up actions are appropriate. Usage is implied rather than guided.

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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