MCP server for YouTubeTranscript-MiniSaaS v2 API. Features transcript creation, batch processing, job polling, and format export.
Server has 5 tools with complete input schemas and descriptions, but quality is uneven. Tool names follow verb_noun convention (transcribe_v2, list_transcripts, get_transcript, get_stats, delete_transcript). Descriptions are present but brief (avg ~80 chars, below 194-char baseline). Parameters are typed with enums where appropriate (source, status fields), but descriptions lack actionable detail on constraints, formats, and dependencies. Output schemas are not documented, LLMs cannot predict response structure. Error handling is minimal; no recovery guidance. Destructive tool (delete_transcript) lacks confirmation pattern. Overall: functional but below production baseline.
POST /api/v1/transcripts/bulk-delete. Delete transcripts by ids or by video_id.
Get stats: credits left, transcripts created, plan, rate limit.
GET /api/v1/transcripts/{video_id}. Get full transcript for a video.
GET /api/v1/history. List or search user transcripts. Use search to find by video id, title, or transcript content.
POST /api/v2/transcribe. Fast caption-based transcript (no ASR). Use manual or auto captions only.
Output schemas not documented. LLMs cannot predict response structure (fields, types, nesting). Agents must guess what get_stats returns or what transcript segments contain.
Destructive tool (delete_transcript) lacks confirmation or dry-run pattern. Agents can permanently delete transcripts without explicit user approval, risking data loss.
Parameter descriptions lack actionable constraints. 'language' param says 'Language tag (e.g. en, en-US)' but does not specify format, valid range, or what happens if invalid. 'limit' in list_transcripts has no min/max bounds.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 58 | 2026-07-28+ | v2 |
get_stats description is vague ('Get stats: credits left, transcripts created, plan, rate limit'). Does not explain when to call it, what the response structure is, or how to interpret rate limit values.
No error recovery guidance. If transcribe_v2 fails (e.g. video not found, no captions available), the tool does not tell the LLM what to do next or which parameters to adjust.