Delete Sample. Removes a sample by its ID.
Bulk support: accepts voice_ids, sample_ids for batched execution.
| Name | Required | Description | Default |
|---|---|---|---|
| account | No | ||
| voice_id | Yes | ||
| sample_id | Yes | ||
| voice_ids | No | ||
| sample_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 indicate destructiveHint=false, but the description says 'Delete Sample' which implies destruction. This is a potential contradiction: the description suggests a destructive action while annotations say it's not destructive. Additionally, no details about irreversibility, permissions, or side effects are provided, and the description doesn't add context beyond the name.
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 concise with two sentences, front-loading the core purpose. The bulk support note is useful and adds value without excessive length. It earns its place, though it could be slightly more structured.
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?
Given the tool has 5 parameters, no output schema, and no annotations beyond basic hints, the description is incomplete. It doesn't explain return values, error conditions, or the exact semantics of bulk vs single deletion. The description is adequate for a simple delete but lacks depth for a tool with multiple parameters and bulk capabilities.
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. It mentions voice_id and sample_id implicitly via 'by its ID' and bulk support via voice_ids and sample_ids, but it doesn't explain the relationship between these parameters (e.g., whether voice_id is required for bulk, or if sample_id alone suffices). The description adds minimal value over the schema.
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 the tool deletes a sample by its ID, which is a specific verb+resource. It distinguishes from siblings like elevenlabs_delete_voice or elevenlabs_delete_pvc_voice_sample by focusing on 'sample' and mentioning bulk support, though it doesn't explicitly differentiate from other delete tools.
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 usage for deleting samples and mentions bulk support, but it doesn't provide explicit when-to-use vs alternatives or exclusions. It doesn't clarify when to use this over elevenlabs_delete_pvc_voice_sample or other delete tools, leaving the agent to infer from the name.
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.