Enables semantic analysis of chat conversations through vector embeddings and knowledge graphs.
Enables semantic analysis of chat conversations through vector embeddings and knowledge graphs.
A Model Context Protocol (MCP) server that enables semantic analysis of chat conversations through vector embeddings and knowledge graphs. This server provides tools for analyzing chat data, performing semantic search, extracting concepts, and analyzing conversation patterns.
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Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.
| Tool | What it does |
|---|---|
| import_conversations | Import and analyze chat conversations python { "source_path": "/path/to/export.zip", "format": "openai_native" # or html, markdown, json } |
| semantic_search | Search conversations by semantic similarity python { "query": "machine learning applications", "limit": 10, "min_score": 0.7 } |
| analyze_metrics | Analyze conversation metrics python { "conversation_id": "conv-123", "metrics": [ "message_frequency", "response_times", "topic_diversity" ] } |
| extract_concepts | Extract and analyze concepts python { "conversation_id": "conv-123", "min_relevance": 0.5, "max_concepts": 10 } |
{
"mcpServers": {
"chat-analysis": {
"command": "uvx",
"args": ["mcp-chat-analysis-server"],
"env": {
"QDRANT_URL": "your-value",
"NEO4J_URL": "your-value",
"NEO4J_USER": "your-value",
"NEO4J_PASSWORD": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| QDRANT_URL | Endpoint or connection string the server talks to. | Yes |
| NEO4J_URL | Endpoint or connection string the server talks to. | Yes |
| NEO4J_USER | Configuration value read at startup. | Optional |
| NEO4J_PASSWORD | Configuration value read at startup. | Optional |
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