elevenlabs_search_groups
Search User Groups. Searches for user groups in the workspace. Multiple or no groups may be returned.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| account | No |
Search User Groups. Searches for user groups in the workspace. Multiple or no groups may be returned.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| account | 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?
Beyond the annotations (readOnlyHint, destructiveHint), the description adds that multiple or no groups may be returned, which is a useful behavioral detail. However, it does not mention parameter behavior, pagination, or any other traits like authentication or rate limits. Since annotations already declare safety, this additional context earns a modest score.
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 but somewhat repetitive: 'Search User Groups' restates the tool name, and 'Searches for user groups in the workspace' repeats the same information. It is not as concise as it could be, but it is not overly verbose. The front-loaded purpose is clear, but the redundancy wastes a sentence.
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 two-parameter search tool with no output schema, the description is incomplete. It does not explain the parameters, which are essential for correct invocation, nor does it clarify the return format beyond saying multiple/none. The annotations help with safety, but the functional semantics are underspecified, leaving the agent guessing.
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?
The schema has two parameters (name and account) with zero description coverage. The tool description does not explain what these parameters are for; it only vaguely implies a search but never connects them to the parameters. This is a critical gap because the agent cannot infer that 'name' likely holds the search term or what 'account' controls.
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 that the tool searches for user groups in the workspace, using the verb 'search' and a specific resource. It also notes that multiple or no groups may be returned. However, it does not differentiate from a sibling tool like elevenlabs_get_groups_endpoint, so it lacks explicit distinction.
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?
There is no guidance on when to use this tool versus alternatives. The description simply states what it does without any context on when it is appropriate or preferable to other group-related tools. No exclusions or alternative tool mentions are given.
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.