The MCP ecosystem often has several independent packages implementing the same tool — and "Youtube Transcript" currently has 12. Every one of them was scanned with the same deterministic engine, so the numbers below are directly comparable: the Trust Score (A–F), the capability blast radius, and how much of the package the scan could actually inspect. They are ranked by score; ties break toward unscoped, longer-established packages.
| Implementation | Package | Trust | Capability | Coverage | Findings | Scanned |
|---|---|---|---|---|---|---|
| Youtube Transcriptbest by kimtaeyoon83 | @kimtaeyoon83/mcp-server-youtube-transcript
npm |
A 99/100 | Minimal | Source | 0 | 2026-09-07 |
| Youtube Transcript by fabriqa.ai | @fabriqa.ai/youtube-transcript-mcp
npm |
A 99/100 | Minimal | Source | 0 | 2026-09-07 |
| Youtube Transcript by tanush-yadav | @tanush-yadav/youtube-transcript-mcp
npm |
A 99/100 | Minimal | Source | 0 | 2026-09-07 |
| Youtube Transcript by emit-ia | @emit-ia/youtube-transcript-mcp
npm |
A 99/100 | Minimal | Source | 0 | 2026-09-07 |
| Youtube Transcript by andy | youtube-transcript-mcp-server
npm |
A 99/100 | Minimal | Source | 0 | 2026-09-07 |
| Youtube Transcript by SeanPedersen | youtube-transcript-mcp-server
PyPI |
A 99/100 | Minimal | Source | 0 | 2026-08-25 |
| Youtube Transcript by PyPI | mcp-youtube-transcript
PyPI |
A 98/100 | Minimal | Source | 0 | 2026-08-25 |
| Youtube Transcript by PyPI | youtube-transcript-mcp
PyPI |
A 98/100 | Minimal | Source | 0 | 2026-08-25 |
| YouTube Transcript by sinco-lab | @sinco-lab/mcp-youtube-transcript
npm |
A 96/100 | Moderate | Source | 1 | 2026-08-25 |
| Youtube Transcript by gabriel3615 | @gabriel3615/mcp-youtube-transcript
npm |
A 96/100 | Moderate | Source | 0 | 2026-09-07 |
| Youtube Transcript by npm | youtube-transcript-mcp
npm |
A 92/100 | High | Source | 2 | 2026-09-07 |
| Youtube Transcript by npm | mcp-youtube-transcript
npm |
B 87/100 | Minimal | Metadata | 0 | 2026-09-07 |
A higher-ranked implementation is not "the official one" — ranking reflects only what the deterministic scan found in each published package. Open an implementation to read its individual findings with evidence, its scan history per version, and to grab an embeddable badge. Scores are automated opinions, recomputed on every rescan.