# Twitter Announcement Thread
## Tweet 1/6 (Hook + Problem)
Ship fewer bugs with ClipSense MCP – the first AI debugging tool that analyzes your screen recordings.
Just record your app crash → paste the video path → get instant AI analysis with root cause + fix suggestions.
Works with React Native, iOS, Android. 9 video formats supported.
## Tweet 2/6 (The Problem)
Debugging mobile apps is brutal:
• Video Loom/bug reports lack technical depth
• Manually scrubbing through crash videos takes hours
• Reproducing bugs is inconsistent
• Claude Desktop has 31MB file limit (99% of videos exceed this)
You need AI that can ACTUALLY analyze your 500MB screen recordings.
## Tweet 3/6 (The Solution)
ClipSense MCP brings AI video analysis directly into your coding workflow:
1. Record bug with QuickTime/iOS/Android
2. Ask Claude Code: "analyze Desktop/crash.mp4"
3. Get frame-by-frame analysis + code fixes in 2 minutes
Powered by Claude Sonnet 4.5. Works in VS Code, Cursor, Windsurf, Continue.dev.
## Tweet 4/6 (Demo/Results)
What you get:
✅ Root cause (e.g., "NullPointerException at ProfileScreen.tsx:142")
✅ Timeline breakdown (frame-by-frame)
✅ Visual evidence (key moments identified)
✅ Code fix suggestions (copy-paste ready)
All without leaving your IDE.
[GIF/Screenshot placeholder]
## Tweet 5/6 (Social Proof + Stats)
Early results:
• 500MB video support (vs Claude Desktop's 31MB)
• 9 video formats (MP4, MOV, WebM, AVI, MKV, FLV, MPEG, 3GP, WMV)
• 2-3 minute processing time
• Works with ALL MCP-compatible AI assistants
Free tier: 3 analyses/month. No credit card.
## Tweet 6/6 (CTA)
Try ClipSense MCP today:
1. Get free API key:
curl -X POST "https://api.clipsense.app/api/v1/keys/request" \\
-H "Content-Type: application/json" \\
-d '{"email":"you@example.com"}'
2. Install: npm install -g @gburanda/clipsense-mcp-server
3. Configure your IDE: https://github.com/clipsense/-mcp-server
Star the repo ⭐
Share your results 🔁
---
## Alternative Thread (More Technical)
### Tweet 1/6
I built ClipSense MCP to solve a problem Claude Desktop can't:
Analyzing 500MB mobile app crash videos with AI.
Result: Frame-by-frame debugging with root cause analysis + code fixes, all inside VS Code/Cursor.
Works with React Native, iOS (Swift), Android (Kotlin).
Open source: github.com/clipsense/-mcp-server
### Tweet 2/6
The problem with existing tools:
❌ Claude Desktop: 31MB file limit
❌ Loom comments: No technical depth
❌ Manual review: Takes hours
❌ Bug reports: Hard to reproduce
Mobile developers NEED AI that can analyze realistic screen recordings (50-500MB).
### Tweet 3/6
How ClipSense MCP works:
1. Use Model Context Protocol to connect Claude to local filesystem
2. Read video file (MP4, MOV, WebM, AVI, MKV, etc.)
3. Upload to Cloudflare R2 (encrypted)
4. Process with Claude Sonnet 4.5 (frame-by-frame vision)
5. Return structured analysis to your IDE
All in ~2 minutes.
### Tweet 4/6
Real example:
User: "Analyze Desktop/app-crash.mp4"
ClipSense returns:
• Root Cause: "Null pointer at ProfileScreen.tsx:142"
• Timeline: "0:15 - profile loads, 0:18 - crash"
• Fix: "Add null check: user?.profile?.avatar ?? DEFAULT_AVATAR"
No context switching. No manual scrubbing.
### Tweet 5/6
Works with ANY MCP-compatible AI assistant:
✅ Claude Code (VS Code)
✅ Cursor
✅ Windsurf
✅ Continue.dev
✅ Cline
✅ Roo-Cline
One config, works everywhere.
9 video formats supported.
500MB max file size.
Free tier: 3 analyses/month.
### Tweet 6/6
Get started:
📦 npm install -g @gburanda/clipsense-mcp-server
🔑 Get free API key: curl -X POST api.clipsense.app/api/v1/keys/request ...
📖 Docs: github.com/clipsense/-mcp-server
Built for React Native, iOS, and Android developers who are tired of manual video debugging.
Star the repo if this helps you ship faster ⭐
---
## Recommended Thread to Post
Use **Alternative Thread** – it's more technical, includes real examples, and shows the technical depth that developer audiences on Twitter appreciate.
## Best Time to Post
- **Weekdays**: Tuesday-Thursday, 9-11 AM PT (12-2 PM ET)
- **Avoid**: Weekends, late evenings
- **Hashtags**: #MCP #Claude #AI #ReactNative #iOSDev #AndroidDev #DevTools
## Engagement Strategy
1. Reply to first comment with link to docs + installation guide
2. Monitor replies for first 2 hours
3. Retweet positive feedback
4. Screenshot and share interesting use cases
5. Cross-post to LinkedIn 24 hours later
## Media Attachments
- Tweet 1: ClipSense logo + demo screenshot
- Tweet 4: GIF showing analysis result OR screenshot of structured output
- Tweet 6: GitHub star button + npm install command screenshot
