A
licenseA
qualityB
maintenanceEnables AI assistants to query YouTube search trend data, including rising topics, video keyword growth, and historical demand, using plain language.
3
1
MIT
katto-mcp
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TDQS
A4.1/5.0
Scored across 29 tools
Disambiguation4/5
Most tools target a clearly distinct resource+action, and the very detailed descriptions help distinguish near-neighbors like create_clip_job vs create_clip and the various re-render variants (dub, translate, adjust, add_hook). However, a couple of pairs genuinely overlap: katto_get_account and katto_get_usage both return plan + monthly quota, and katto_get_job vs katto_get_clips both surface clip data, so an agent may hesitate between them.
Naming Consistency5/5
Every tool follows the same katto_ prefix plus verb_noun convention (get_job, list_jobs, create_clip_job, publish_clip, cancel_scheduled_post, etc.), with no mixing of camelCase, tense, or verb styles. The pattern is fully predictable across all 29 tools.
Tool Count3/5
29 tools is on the heavy side for this surface, and a few are near-duplicates (get_job/get_clips, get_account/get_usage) that could be consolidated. Still, the domain is genuinely broad (clipping, rendering, dubbing, publishing, scheduling, uploads, billing), so most tools do earn their place rather than being filler.
Completeness4/5
The core lifecycle is well covered: submit/upload, monitor, list/cancel jobs, derive clips, re-render/dub/translate/adjust, publish, schedule, and manage scheduled posts, plus supporting reads (usage, transcripts, sources, styles). Minor gaps exist — brand kits are read-only, and there is no job/clip deletion — but agents can work around these.
Maintenance
ActivityActive
ResponsivenessUnresponsive