
web-summary
by pacphi
Consistent dev environments anywhere. Define once in YAML, deploy to Docker, Fly.io, or DevPod. Pre-built extensions for AI, languages & infrastructure.
SKILL.md
name: web-summary description: > Summarize web content including YouTube videos with semantic topic links for Logseq and Obsidian. Uses Z.AI service (port 9600) for cost-effective summarization. Supports markdown, plain text, and note-taking formats. version: 2.0.0 author: turbo-flow-claude mcp_server: true protocol: fastmcp entry_point: mcp-server/server.py dependencies:
- httpx
- youtube-transcript-api
Web Summary Skill
URL content summarization and topic extraction via FastMCP, using Z.AI service for LLM processing.
When to Use This Skill
- Summarize web articles, blog posts, documentation
- Extract and summarize YouTube video transcripts
- Generate semantic topic links for note-taking (Logseq, Obsidian)
- Create short, medium, or long summaries
- Extract key concepts from text
Architecture
┌─────────────────────────────┐
│ Claude Code / VisionFlow │
│ (MCP Client) │
└──────────────┬──────────────┘
│ MCP Protocol (stdio)
▼
┌─────────────────────────────┐
│ Web Summary MCP Server │
│ (FastMCP - Python only) │
└──────────────┬──────────────┘
│ HTTP (port 9600)
▼
┌─────────────────────────────┐
│ Z.AI Service │
│ (Cost-effective Claude) │
└─────────────────────────────┘
Tools
| Tool | Description |
|---|---|
summarize_url | Summarize content from any URL (web or YouTube) |
youtube_transcript | Extract full transcript from YouTube video |
generate_topics | Generate semantic topic links from text |
health_check | Verify Z.AI service connectivity |
Examples
# Summarize a web article
summarize_url({
"url": "https://example.com/article",
"length": "medium",
"include_topics": True,
"format": "logseq"
})
# Get YouTube transcript
youtube_transcript({
"video_id": "dQw4w9WgXcQ", # or full URL
"language": "en"
})
# Generate topic links
generate_topics({
"text": "Your text content here...",
"max_topics": 10,
"format": "obsidian"
})
Output Formats
Logseq
- [[Topic One]]
- [[Topic Two]]
- [[Machine Learning]]
Obsidian
- [[Topic One]]
- [[Topic Two]]
- [[Machine Learning]]
Plain
- Topic One
- Topic Two
- Machine Learning
Environment Variables
| Variable | Default | Description |
|---|---|---|
ZAI_URL | http://localhost:9600/chat | Z.AI service endpoint |
ZAI_TIMEOUT | 60 | Request timeout in seconds |
Troubleshooting
Z.AI connection failed:
# Check Z.AI service status
supervisorctl status claude-zai
# Test Z.AI directly
curl -X POST http://localhost:9600/chat \
-H "Content-Type: application/json" \
-d '{"prompt": "Hello"}'
VisionFlow Integration
This skill exposes web-summary://capabilities resource for discovery by VisionFlow's MCP TCP client on port 9500.
Score
Total Score
Based on repository quality metrics
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Reviews
Reviews coming soon

