Get Music Finetunes. List music finetunes accessible to you (your own, workspace-shared, and ElevenLabs-curated), with optional filtering, sorting, and cursor pagination.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | ||
| cursor | No | ||
| account | No | ||
| page_size | No | ||
| created_by | No | ||
| visibility | No | ||
| sort_direction | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description need not restate safety. It adds useful behavioral context: what set of finetunes is listed and what features are available (filtering, sorting, cursor pagination). No contradiction exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence. It states the resource and purpose immediately, then adds scope and feature details with no filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 7 parameters and no output schema, the description covers the core list purpose, accessible scope, and high-level capabilities. However, it omits details about return shape, cursor mechanics, and the meaning of the account parameter. Annotations supply safety semantics but not enough to make the description fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description needed to compensate. It mentions filtering, sorting, and cursor pagination generically, but it does not explain specific parameters like account, page_size, or how cursor should be supplied. The schema's enum values and property names carry some meaning, but the description adds little parameter-level guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List music finetunes accessible to you' with a specific verb and resource, and enumerates the scope: own, workspace-shared, and ElevenLabs-curated. This distinguishes it from sibling tools like elevenlabs_get_finetune, update_finetune, and delete_finetune.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: it is a read-only list operation over accessible finetunes, with optional filtering, sorting, and pagination. It does not explicitly mention when to prefer this over elevenlabs_get_finetune, so it stops short of a full when-to-use vs. alternatives statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
There are many tools with overlapping purposes, such as multiple voice retrieval tools (get_voice_by_id, get_voices, get_user_voices_v2, get_library_voices) and several dubbing transcript segment editors with only subtle naming differences. The inclusion of platform-level tools (authenticate, connect, marketplace) alongside ElevenLabs API tools further blurs boundaries.
Naming is highly inconsistent. Most tools have the 'elevenlabs_' prefix, but some do not (authenticate, connect, marketplace, report_bug, show_version, toolkit_info). Several tools have truncated/random suffix names (e.g., elevenlabs_dubbing_target_transcript_segmen_b565e6, elevenlabs_get_pronunciation_dictionary_ver_45baf2), and one tool is in Portuguese (elevenlabs_list_accounts). This mixture of conventions and languages makes the pattern unpredictable.
With 155 tools, the server is extremely bloated. It mixes a comprehensive ElevenLabs API surface with unrelated MCP platform tools (marketplace, authenticate, report_bug, etc.) that belong in a separate toolkit. This is a severe mismatch between the apparent purpose (ElevenLabs audio services) and the sheer number of tools.
The ElevenLabs-specific tools cover a wide range of operations (text-to-speech, voice management, dubbing, pronunciation dictionaries, Studio projects, workspace administration, order management), making it fairly complete for those domains. However, the inclusion of unrelated platform tools and the lack of a clear focus mean that an agent would have difficulty navigating this large surface, and some operations like music finetuning or speech engines appear only partially covered.