Youtube Summarizer

Why This vs ChatGPT?

Problem with ChatGPT: It can't access YouTube transcripts directly. You have to manually copy/paste captions or use a third-party tool first, then feed the text to ChatGPT. Multi-step, clunky, loses video metadata.

This skill provides:

1. One-step transcript extraction - Drop a YouTube URL, get the full transcript automatically
2. Structured summarization - Consistent format (thesis → insights → takeaway) every time, not random bullet points
3. Video metadata included - Title, channel, views, publish date embedded in summary
4. Full transcript delivery - Saves timestamped transcript to file and sends to Telegram/chat platforms
5. Works from VPS/cloud - Uses Android client emulation to bypass YouTube's cloud IP blocking (where yt-dlp fails)
6. Multi-language support - Auto-fetches in requested language with English fallback

You can replicate this by manually enabling captions, copying text, pasting to ChatGPT, reformatting the output, saving to a file, and uploading. Takes 5-10 minutes. This skill does it in 15-20 seconds.

When to Use

Activate this skill when:

• User shares a YouTube URL (youtube.com/watch, youtu.be, youtube.com/shorts)
• User asks to summarize or transcribe a YouTube video
• User requests information about a YouTube video's content
• You need to analyze video content for research or content creation

Dependencies

Required: MCP YouTube Transcript server must be installed at: ~/mcp-server-youtube-transcript

If not present, install it:

cd ~
git clone https://github.com/kimtaeyoon83/mcp-server-youtube-transcript.git
cd mcp-server-youtube-transcript
npm install && npm run build

Workflow

1. Detect YouTube URL

Extract video ID from these patterns:

• https://www.youtube.com/watch?v=VIDEO_ID
• https://youtu.be/VIDEO_ID
• https://www.youtube.com/shorts/VIDEO_ID
• Direct video ID: VIDEO_ID (11 characters)

2. Fetch Transcript

Run this command to get the transcript:

cd ~/mcp-server-youtube-transcript && node --input-type=module -e "
import { getSubtitles } from './dist/youtube-fetcher.js';
const result = await getSubtitles({ videoID: 'VIDEO_ID', lang: 'en' });
console.log(JSON.stringify(result, null, 2));
" > /tmp/yt-transcript.json

Replace VIDEO_ID with the extracted ID. Read the output from /tmp/yt-transcript.json.

3. Process the Data

Parse the JSON to extract:

• result.metadata.title - Video title
• result.metadata.author - Channel name
• result.metadata.viewCount - Formatted view count
• result.metadata.publishDate - Publication date
• result.actualLang - Language used
• result.lines - Array of transcript segments

Full text: result.lines.map(l => l.text).join(' ')

4. Generate Summary

Create a structured summary using this template:

📹 **Video:** [title]
👤 **Channel:** [author] | 👁️ **Views:** [views] | 📅 **Published:** [date]

**🎯 Main Thesis:**
[1-2 sentence core argument/message]

**💡 Key Insights:**
- [insight 1]
- [insight 2]
- [insight 3]
- [insight 4]
- [insight 5]

**📝 Notable Points:**
- [additional point 1]
- [additional point 2]

**🔑 Takeaway:**
[Practical application or conclusion]

Aim for:

• Main thesis: 1-2 sentences maximum
• Key insights: 3-5 bullets, each 1-2 sentences
• Notable points: 2-4 supporting details
• Takeaway: Actionable conclusion

5. Save Full Transcript

Save the complete transcript to a timestamped file:

~/transcripts/YYYY-MM-DD_VIDEO_ID.txt

Include in the file:

• Video metadata header (title, channel, URL, date)
• Full transcript text
• URL reference for easy lookup

6. Platform-Specific Delivery

If channel is Telegram:

message --action send --channel telegram --target CHAT_ID \
  --filePath ~/transcripts/YYYY-MM-DD_VIDEO_ID.txt \
  --caption "📄 YouTube Transcript: [title]"

If channel is other/webchat: Just reply with the summary (no file attachment).

7. Reply with Summary

Send the structured summary as your response to the user.

Real Case Study

User: Content creator researching competitor YouTube strategies

Challenge: Needed to analyze 20+ competitor videos per week to identify trending topics, messaging patterns, and content gaps. Manual process: watch video, take notes, transcribe key quotes. Time: 30-45 min per video.

Solution with youtube-summarizer:

1. Drop YouTube URL in chat
2. Get structured summary in 20 seconds
3. Full transcript saved for reference
4. Copy key insights for content planning doc

Workflow example:

User: Analyze this video: https://youtube.com/watch?v=abc123
[20 seconds later]

📹 Video: "10 AI Tools That Will Replace Your Job in 2026"
👤 Channel: TechFuturist | 👁️ Views: 847K | 📅 Published: Jan 12, 2026

🎯 Main Thesis:
AI tools are automating creative and knowledge work faster than expected, but the real opportunity is in augmentation, not replacement.

💡 Key Insights:
- ChatGPT usage among marketers jumped from 12% to 67% in one year
- Video editing time reduced by 80% using AI tools like Descript
- The biggest wins come from combining tools (Notion + Claude + Zapier)
- Companies hiring "AI workflow designers" to optimize human-AI collaboration
- Workers using AI secretly outperform peers by 40% (BCG study)

📝 Notable Points:
- Shows examples of 3 small businesses that 10× output with AI
- Warns against over-automation: "AI can write, but can't think strategically"

🔑 Takeaway:
Don't ask "Will AI replace me?" Ask "How can I use AI to become 10× more valuable?"

Results after 8 weeks:

• Time saved: 25 hours/week (from 600 min to 60 min for 20 videos)
• Content output: 3 videos/week (up from 1/week)
• Better insights: Full transcripts searchable, found patterns missed when just watching
• Competitive intel: Built database of 160+ competitor video summaries with key quotes
• ROI quote: "This skill turned competitor research from a chore into an assembly line."

Why This Beats Manual Methods

Error Handling

If transcript fetch fails:

• Check if video has captions enabled
• Try with lang: 'en' fallback if requested language unavailable
• Inform user that transcript is not available and suggest alternatives:
  • Manual YouTube transcript feature (Settings → Show transcript)
  • Video may not have captions
  • Try a different video

If MCP server not installed:

• Provide installation instructions
• Offer to install it automatically if in appropriate context

If video ID extraction fails:

• Ask user to provide the full YouTube URL or video ID

If video is age-restricted or private:

• Inform user that transcript cannot be accessed due to restrictions
• Suggest checking video privacy settings

Examples

Example 1: Tech Tutorial

Input: https://youtube.com/watch?v=dQw4w9WgXcQ

Output:

📹 **Video:** "Building a SaaS from Scratch: Lessons from $10K MRR"
👤 **Channel:** IndieHackerTV | 👁️ **Views:** 124K | 📅 **Published:** Feb 1, 2026

**🎯 Main Thesis:**
Most SaaS founders fail because they build for 6 months before talking to customers. The path to $10K MRR is customer conversations first, MVP second.

**💡 Key Insights:**
- Interviewed 50 potential customers before writing a single line of code
- First paid customer signed up with a Figma mockup (no product built yet)
- Charged $99/month from day 1 (no free tier, no discounts)
- Spent $0 on ads; all growth from Twitter + Reddit engagement
- Hit $10K MRR in 9 months by saying "no" to feature requests that didn't fit ICP

**📝 Notable Points:**
- Used Stripe payment links before building a billing system
- First 3 customers came from solving their problem in public on Twitter
- Weekly "build in public" updates on Twitter drove 40% of signups

**🔑 Takeaway:**
Validate demand before building. If 10 people won't pay for a mockup, 1,000 won't pay for the real product.

Example 2: Business Strategy Video

Input: https://youtu.be/abc123xyz

Output:

📹 **Video:** "Why Notion's Business Model is Genius"
👤 **Channel:** SaaS Breakdowns | 👁️ **Views:** 456K | 📅 **Published:** Jan 28, 2026

**🎯 Main Thesis:**
Notion's growth strategy flips traditional SaaS: give away the product for free to individuals, monetize when they bring it to work.

**💡 Key Insights:**
- 80% of Notion's enterprise deals started with a single employee using the free plan
- Bottom-up adoption = zero sales team needed for first $10M ARR
- Templates marketplace created a content flywheel (100K+ free templates)
- Personal use (free) → Team use (paid) conversion rate: 23% (industry avg: 2-5%)
- Community evangelism replaced traditional marketing (4M+ Reddit/Discord members)

**📝 Notable Points:**
- Notion's viral coefficient: 1.4 (every user invites 1.4 others on average)
- Template creators drive 30% of new user acquisition
- Pricing strategy: free until 10 people = no friction to start

**🔑 Takeaway:**
Build a product individuals love first. Enterprise sales will follow when employees demand it at work.

Quality Guidelines

• Be concise: Summary should be scannable in 30 seconds
• Be accurate: Don't add information not in the transcript
• Be structured: Use consistent formatting for easy reading
• Be contextual: Adjust detail level based on video length
  • Short videos (<5 min): Brief summary (3 key insights)
  • Medium videos (5-30 min): Standard format (5 key insights)
  • Long videos (>30 min): Detailed breakdown (7+ insights, split into sections if needed)
• Extract value: Focus on actionable insights, data points, and contrarian takes (not generic advice)

Pro Tips

For Better Summaries:

1. Prioritize data points - Numbers, percentages, study citations stand out
2. Extract quotes - Memorable one-liners make summaries shareable
3. Identify frameworks - If video presents a method/process, extract the steps
4. Spot contrarian takes - Unconventional wisdom is more valuable than common advice
5. Note proof - Examples, case studies, before/after results add credibility

For Research Workflows:

1. Build a transcript library - Organize by topic/niche for pattern spotting
2. Search across transcripts - Use grep or text search to find mentions of specific topics
3. Track trends - Same topic across multiple videos = rising trend
4. Extract prompts - Save useful frameworks/methods as reusable prompts

For Content Creation:

1. Find content gaps - What questions are asked but not fully answered?
2. Analyze top performers - What structure/pacing do high-view videos use?
3. Extract hooks - First 30 seconds of transcript = proven hook patterns
4. Repurpose insights - Turn video insights into Twitter threads, blog posts, newsletters

Configuration

Standard Mode (default)

youtube-summarizer [URL]

• Fetches transcript in English
• Generates structured summary
• Saves transcript to file
• Sends to messaging platform if applicable

Quick Mode

youtube-summarizer [URL] --quick

• Thesis + 3 key insights only
• No transcript file saved
• Faster processing for rapid research

Deep Dive Mode

youtube-summarizer [URL] --deep

• Extended summary with timestamps
• Section-by-section breakdown for long videos
• Includes all notable quotes

Language-Specific

youtube-summarizer [URL] --lang es

• Fetches transcript in specified language
• Falls back to English if unavailable

Installation & Setup

# 1. Clone and install MCP server
cd ~
git clone https://github.com/kimtaeyoon83/mcp-server-youtube-transcript.git
cd mcp-server-youtube-transcript
npm install && npm run build

# 2. Test installation
node --input-type=module -e "
import { getSubtitles } from './dist/youtube-fetcher.js';
const result = await getSubtitles({ videoID: 'dQw4w9WgXcQ', lang: 'en' });
console.log(result.metadata.title);
"

# 3. Create transcripts directory
mkdir -p ~/transcripts

# 4. Verify skill is ready
youtube-summarizer --check-setup

Common Issues

Issue: "Transcript not available"

• Cause: Video has no captions/subtitles enabled
• Fix: Ask video creator to enable captions, or try a different video

Issue: "Failed to fetch transcript" (on VPS)

• Cause: YouTube may have updated their API
• Fix: Update MCP server: cd ~/mcp-server-youtube-transcript && git pull && npm install && npm run build

Issue: "Video ID not recognized"

• Cause: Malformed URL or unsupported format
• Fix: Copy URL directly from YouTube address bar

Future Enhancements (Roadmap)

• Multi-video batch processing (analyze playlists)
• Sentiment analysis on transcript (positive/negative/neutral tone)
• Speaker diarization (identify different speakers in interviews/panels)
• Automatic chapter detection (split long videos into logical sections)
• Cross-video pattern analysis (find common themes across multiple videos)

Support

Issues or suggestions? Provide:

• YouTube URL that failed
• Error message (if any)
• Expected vs actual behavior
• MCP server version: cd ~/mcp-server-youtube-transcript && git rev-parse HEAD

Built on MCP YouTube Transcript server (Android emulation for cloud reliability). Turn any YouTube video into structured, searchable knowledge in 20 seconds.