networklytics-mcp
networklytics-mcp
NetworkLytics MCP-Server (Model Context Protocol).
Sie können die Ergebnisse der YouTube-Kommentar-Netzwerkanalyse direkt in MCP-unterstützten KI-Tools wie Claude Desktop oder Cursor abrufen.
Installation
pip install networklytics-mcpRelated MCP server: vidlens-mcp
Konfiguration für Claude Desktop
Fügen Sie dies zu ~/.claude/claude_desktop_config.json oder %APPDATA%\Claude\claude_desktop_config.json hinzu:
{
"mcpServers": {
"networklytics": {
"command": "networklytics-mcp",
"env": {
"NETWORKLYTICS_API_URL": "https://networklytics.com",
"NETWORKLYTICS_API_KEY": "nly_your_api_key_here"
}
}
}
}Den API-Schlüssel erhalten Sie auf der Seite mit Ihren NetworkLytics-Kontoeinstellungen.
Anwendungsbeispiele
Sie können Claude wie folgt fragen:
"Zeige mir die Analyseergebnisse für diesen geteilten Link: https://networklytics.com/shared/abc-123-..."
"Finde die 3 wichtigsten Influencer in den Analyseergebnissen"
"Wie ist der Sentiment-Trend in der Kommentar-Community dieses YouTube-Kanals?"
Verfügbare Tools
Tool | Beschreibung | Authentifizierung |
| Analyseergebnisse über einen geteilten Link-Token abrufen | Nicht erforderlich |
| Ergebnisse über die Analyse-ID abrufen | API-Schlüssel erforderlich |
| API-Informationen und Endpunktliste | Nicht erforderlich |
Struktur der zurückgegebenen Daten
{
"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": { ... }
}Maintenance
Resources
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