@runapi.ai/runway-aleph-mcp
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TDQS
Scored across 4 tools
Each tool targets a distinct action and resource: login (auth), edit_video (create task), get_task (poll task), and check_pricing (billing info). There is no meaningful overlap, so an agent can select the right tool unambiguously.
Three tools follow a clean verb_noun pattern (edit_video, get_task, check_pricing), while login uses only a verb with no noun. This is a minor deviation but the set remains readable and predictable.
Four tools cover the minimal lifecycle of auth, task creation, task polling, and pricing lookup. It is slightly lean but still reasonable for a narrowly scoped async video-editing API, with no redundant tools.
The core create-and-poll workflow is present, but notable task-management operations like cancel_task, list_tasks, or fetching/exporting output assets are missing. Agents can complete basic edits but lack lifecycle control beyond polling and no way to clean up or browse tasks.