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@aiwerk/mcp-server-elevenlabs

@aiwerk/mcp-server-elevenlabs

by AIWerk
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

convert_chapter_endpoint

Converts a chapter in an ElevenLabs Studio project using its project ID and chapter ID, spending credits to process it.

Instructions

Convert Chapter Spends ElevenLabs credits.

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": {
      "project_id": "<project_id>",
      "chapter_id": "<chapter_id>"
    },
    "name": "convert_chapter_endpoint"
  }
}

Input Schema

NameRequiredDescriptionDefault
chapter_idYesThe ID of the chapter.
project_idYesThe ID of the Studio project.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false, idempotentHint=false, and openWorldHint=true. The description adds one useful behavioral fact beyond annotations: the operation consumes ElevenLabs credits. However, it does not explain what conversion does, whether it is long-running, or whether it requires specific account state.

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 a single compact sentence fragment with no filler, and the key information is front-loaded. It is slightly awkward grammatically, but it does not waste space.

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

Completeness2/5

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

For a non-readonly, open-world, credit-consuming mutation tool, the description is very thin. It does not explain prerequisites, output, expected result, or what happens to the chapter, and the absence of an output schema leaves the agent without enough context to call it confidently.

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 both chapter_id and project_id are already documented in the input schema. The description adds no parameter-level meaning beyond what the schema provides, so the baseline score of 3 is appropriate.

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 names a specific verb and resource (Convert Chapter) and adds that the operation spends ElevenLabs credits. It is clear enough to identify the action, but it does not distinguish this tool from the sibling convert_project_endpoint or explain what the conversion produces.

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?

There is no explicit when-to-use guidance, no when-not-to-use guidance, and no mention of the alternative convert_project_endpoint. The agent must infer usage context entirely from the tool name.

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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