Add Member To User Group. Adds a member of your workspace to the specified group. Requires group_members_manage permission.
Bulk support: accepts group_ids for batched execution.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | |||
| account | No | ||
| group_id | Yes | ||
| group_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 indicate this is a mutating operation (readOnlyHint=false) and not destructive. The description adds the permission requirement and bulk support, which are not covered by annotations. But it does not disclose side effects like what happens if the member already exists in the group, or any rollback/reversibility. Since annotations provide a baseline, the extra permission info justifies a 3.
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 extremely efficient: two sentences that convey the core action, permission, and an optional bulk feature. No filler or redundancy. Perfectly front-loaded.
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 simple mutation tool with no output schema, the description covers the main action and permission, plus bulk capability. However, it lacks details on return values, edge cases (duplicate members), and any potential side effects. Given the simplicity, it's minimally adequate but not rich.
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 only explicitly explains 'group_ids' for bulk execution. The required parameters 'email' and 'group_id' are implied but not defined, and 'account' is completely unexplained. This is insufficient for an agent to correctly construct parameters, so a low score is warranted.
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 action: 'Adds a member of your workspace to the specified group.' This is a specific verb and resource, and it distinguishes from sibling tools like elevenlabs_remove_member and elevenlabs_invite_user. The title 'Add Member To User Group' reinforces the purpose.
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 explains the permission required ('group_members_manage'), which gives a usage prerequisite. It implies this tool is for adding existing workspace members to groups, and the bulk support note clarifies an alternative usage. However, it does not explicitly contrast with other member-management tools (e.g., invite_user), so it earns a 4 rather than a 5.
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.