Update Dubbing Transcript Segments. Enterprise only. Edit several source segments' text, speaker, or timing in one atomic request.
Bulk support: accepts project_ids for batched execution.
| Name | Required | Description | Default |
|---|---|---|---|
| account | No | ||
| segments | Yes | ||
| project_id | Yes | ||
| project_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 indicate a write operation (readOnlyHint false). The description adds useful context: 'Enterprise only' (access constraint), 'atomic request' (all-or-nothing behavior), and 'bulk support' (batched execution). These go beyond annotations, but it doesn't disclose potential side effects, reversibility, or detailed behavior on failure beyond atomicity.
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 concise with four short sentences, each adding distinct value: purpose, enterprise restriction, core functionality, and bulk support. There is no redundant text, and key information is 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?
Given the tool's complexity (nested segments object, optional project_ids, atomic behavior) and lack of an output schema, the description is incomplete. It does not explain how to construct segments, what fields are editable in detail, error/response behavior, or prerequisites beyond enterprise status. The schema is vague, so more descriptive guidance is needed.
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 mentions editing 'text, speaker, or timing' (hinting at segments content) and explains project_ids for bulk execution, but does not explain the 'account' parameter or the structure/format of the 'segments' object. This is inadequate for a 0% coverage parameter set.
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 it updates dubbing transcript segments, with a specific verb ('Update') and resource. It further specifies editing 'text, speaker, or timing' and distinguishes from the singular sibling tool by emphasizing 'several source segments' and 'atomic request'.
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?
It provides context that this tool is for editing multiple segments at once and mentions bulk support via project_ids. However, it does not explicitly contrast with the singular segment update tool or state when not to use it, though the plural naming and bulk hints imply use for multi-segment operations.
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.