networklytics-mcp
YouTube comment social network analysis (SNA): influencer centrality ranking, community detection (Louvain algorithm), sentiment analysis, and AI-generated insights via public JSON API.
README
networklytics-mcp
NetworkLytics MCP (Model Context Protocol) server.
Claude Desktop, Cursor 등 MCP 지원 AI 도구에서 YouTube 댓글 네트워크 분석 결과를 직접 조회할 수 있습니다.
설치
pip install networklytics-mcp
Claude Desktop 설정
~/.claude/claude_desktop_config.json 또는 %APPDATA%\Claude\claude_desktop_config.json에 추가:
{
"mcpServers": {
"networklytics": {
"command": "networklytics-mcp",
"env": {
"NETWORKLYTICS_API_URL": "https://networklytics.com",
"NETWORKLYTICS_API_KEY": "nly_your_api_key_here"
}
}
}
}
API 키는 NetworkLytics 계정 설정 페이지에서 발급받을 수 있습니다.
사용 예시
Claude에서 다음과 같이 요청할 수 있습니다:
- "이 공유 링크 분석 결과를 보여줘: https://networklytics.com/shared/abc-123-..."
- "분석 결과에서 핵심 인플루언서 3명을 찾아줘"
- "이 YouTube 채널 댓글 커뮤니티의 감성 트렌드는 어때?"
제공 도구 (Tools)
| Tool | 설명 | 인증 |
|---|---|---|
get_shared_analysis |
공유 링크 토큰으로 분석 결과 조회 | 불필요 |
get_analysis_by_id |
분석 ID로 결과 조회 | API 키 필요 |
get_api_info |
API 정보 및 엔드포인트 목록 | 불필요 |
반환 데이터 구조
{
"video": { "title": "...", "channel": "...", "view_count": 123456 },
"network": {
"total_nodes": 1500,
"total_edges": 3200,
"density": 0.003,
"community_count": 7
},
"sentiment": {
"positive_ratio": 0.62,
"negative_ratio": 0.15,
"overall": "positive"
},
"top_influencers": [
{ "author": "username", "degree_centrality": 0.12, "comment_count": 45 }
],
"topic_keywords": ["키워드1", "키워드2"],
"ai_insights": { ... }
}
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