@runapi.ai/gemini-omni-mcp
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TDQS
Scored across 6 tools
Each tool targets a fairly distinct action (auth, pricing lookup, task polling, and three generation endpoints), so an agent can mostly pick correctly. The main blur is between the synchronous create_character/create_audio operations and the task-based text_to_video + get_task flow, since it's unclear whether the sync creates also produce task ids that get_task can poll.
Names mix three conventions: verb_noun (create_character, create_audio, get_task), verb_noun for a non-resource (check_pricing), a bare verb (login), and a noun-phrase endpoint name (text_to_video). It's still readable, but there is no single predictable pattern across all six.
Six tools is well-scoped for a thin wrapper around one model line: auth, pricing, three generation entry points, and task polling. Nothing feels padded or redundant.
Core lifecycle is only partly covered: generation plus get_task exists, but there is no cancel_task, list_tasks, or bulk status retrieval, and login has no matching logout/config-status tool. The asymmetric model (two sync ops vs one async op) also leaves unclear how results of the sync operations are re-fetched.