Get Service Account Api Keys Route. Get all API keys for a service account
Bulk support: accepts service_account_user_ids for batched execution.
| Name | Required | Description | Default |
|---|---|---|---|
| account | No | ||
| service_account_user_id | Yes | ||
| service_account_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 declare readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read operation. The description adds the batching behavior via service_account_user_ids. However, it doesn't mention rate limits, auth requirements, pagination, or response shape.
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 it repeats the tool name ('Get Service Account Api Keys Route'), and the second sentence on bulk support is vague without explaining how the bulk parameter works. It is front-loaded but offers minimal informative content.
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 zero schema description coverage and no output schema, the description should compensate by clarifying parameter semantics (e.g., what service_account_user_ids is for, how bulk execution behaves) and the relationship to sibling tools. None of that is present.
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% — the description mentions service_account_user_ids for bulk support but does not explain service_account_user_id, its format, or the distinction between singular and plural parameters. The description adds little value beyond what the parameter names convey.
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?
Description names the verb (get) and resource (API keys for a service account), which is clear from 'Get all API keys for a service account'. Sibling tools with different verbs (create/edit/delete) make its purpose distinct enough, though the description doesn't explicitly differentiate from them.
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?
No guidance on when to use this tool versus alternatives like elevenlabs_create_service_account_api_key or elevenlabs_edit_service_account_api_key. The description is purely a statement of what the tool does, with no context about scenarios 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.