Add Shared Voice. Add a shared voice to your collection of voices.
Bulk support: accepts public_user_ids, voice_ids for batched execution.
| Name | Required | Description | Default |
|---|---|---|---|
| account | No | ||
| new_name | Yes | ||
| voice_id | Yes | ||
| voice_ids | No | ||
| bookmarked | No | ||
| public_user_id | Yes | ||
| public_user_ids | 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 communicate that this is a write operation and not destructive. The description adds some behavioral context by stating the voice is added to 'your collection' and mentioning batched execution via plural parameters, but it does not disclose naming-conflict behavior, permissions, or reversibility.
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 short and front-loaded, with the core purpose in the first sentence and the bulk capability in the final sentence. The only minor issue is that 'Add Shared Voice' redundantly repeats the tool name, but overall it is efficient.
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?
With 7 parameters, no output schema, and no parameter descriptions, this description is too sparse. It does not explain required versus optional usage, batch semantics in detail, account targeting, or expected outcomes, making it incomplete for reliable invocation.
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 must compensate, but it only mentions public_user_ids and voice_ids for bulk support. It fails to explain required fields like new_name, or optional ones like account and bookmarked, and does not clarify the relationship between singular and plural parameters.
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 uses a specific verb and resource: 'Add a shared voice to your collection of voices.' This clearly distinguishes the action from sibling tools like elevenlabs_create_voice, which creates a new voice, while this tool imports an existing shared voice.
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 implies the usage context—adding shared voices to a personal collection—and notes bulk execution support. However, it gives no explicit guidance on when to prefer this tool over alternatives such as create_voice, nor any exclusions or prerequisites.
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.