@runapi.ai/elevenlabs-mcp
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TDQS
Scored across 8 tools
Each tool has a clearly distinct purpose: authentication, pricing, task status, and five different ElevenLabs task types (speech, sound, dialogue, transcription, source isolation). No overlap or ambiguity between tools.
The tool names mix two patterns: verb_noun (get_task, login, isolate_audio, check_pricing) and noun_to_noun (speech_to_text, text_to_dialogue, text_to_sound, text_to_speech). While each group is internally consistent, the coexistence of two patterns reduces predictability.
With 8 tools, the server is well-scoped for its purpose: covering authentication, pricing, status polling, and five core ElevenLabs task types. No redundant or unnecessary tools; the count fits the ideal range.
The set covers the main lifecycle: creating various task types, fetching status/results, authenticating, and checking pricing. Missing a cancel or list operation is a minor gap that agents can work around, but the core workflow is complete.