Disable Api Key. Disable the API key used to authenticate this request. Requires the query parameter api_key_name=self as an explicit confirmation.
| Name | Required | Description | Default |
|---|---|---|---|
| account | No | ||
| api_key_name | Yes |
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 include readOnlyHint=false and destructiveHint=false, but no idempotentHint (false). The description does not contradict these. It adds a critical behavioral note: 'Requires the query parameter api_key_name=self as an explicit confirmation', which implies a safeguard. However, it does not elaborate on consequences (e.g., irreversible? immediate effect? impact on existing requests?). Given annotations are sparse, description could do more to clarify what 'disable' entails.
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?
Two sentences, concise and to the point. No wasted words. The critical requirement is highlighted. Excellent structure.
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?
The tool is a mutating action (disable) with no output schema and incomplete parameter semantics. It does not explain what happens after disabling (e.g., response, further authentication needs, reversibility). The description does not mention any prerequisites (e.g., being authenticated) or edge cases. Given the complexity of API key management, this is under-specified.
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 description must explain parameters. It only mentions the required parameter `api_key_name` and its specific value 'self', but does not explain the `account` parameter. The parameter semantics for `account` are entirely absent, leaving the agent guessing its purpose. For a 2-parameter tool with zero coverage, this is insufficient.
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's action: 'Disable Api Key' with specific reference to the API key used for the request. It distinguishes from siblings (e.g., delete_service_account_api_key, edit_service_account_api_key) by indicating this disables rather than deletes or edits. However, it could be more explicit that this is a singular action on the current key.
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. It states a requirement ('Requires the query parameter api_key_name=self') but does not explain scenarios where disabling is appropriate, or alternatives like deletion or editing. Sibling tools with similar purposes are not mentioned.
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.