Get Resource. Gets the metadata of a resource by ID.
Bulk support: accepts resource_ids for batched execution.
| Name | Required | Description | Default |
|---|---|---|---|
| account | No | ||
| resource_id | Yes | ||
| resource_ids | No | ||
| resource_type | 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 already indicate readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds the useful behavioral detail of bulk execution via resource_ids, but it does not disclose response shape, error behavior, permissions, or account scoping. It does not contradict annotations.
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 very short and front-loaded. The opening 'Get Resource.' is near-redundant filler, but the remaining two sentences are efficient and directly communicate the core action and bulk capability.
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?
This tool spans a huge enum of resource types and has no output schema, yet the description says nothing about return values, the meaning of 'account', or why an agent might choose this over specific getters. The annotations cover safety, but the description is too minimal for the tool's breadth and ambiguity.
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, but it only mentions 'by ID' and 'resource_ids' for batch. The 'account' parameter is completely unexplained, and the relationship between resource_id and resource_ids is unclear. The schema's enum adds resource_type meaning, but key parameter semantics remain missing.
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 core function: 'Gets the metadata of a resource by ID.' This is a specific verb+resource+scope pairing. However, it does not differentiate itself from the many specific getter siblings like elevenlabs_get_voice_by_id or elevenlabs_get_project_by_id, so it stops short of full 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?
The description provides no guidance on when to use this generic metadata tool versus the numerous more specific getter tools. The 'Bulk support' note hints at one usage scenario, but there are no explicit selection criteria, exclusions, or references to alternatives.
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.