GitHub Stats

    Stars

    10

    Forks

    2

    Release Date

    4/10/2025

    about 2 months ago

    Detailed Description

    MCP Chat Analysis Server

    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.

    Key Features

    • 🔍 Semantic Search: Find relevant messages and conversations using vector similarity
    • 🕸️ Knowledge Graph: Navigate relationships between messages, concepts, and topics
    • 📊 Conversation Analytics: Analyze patterns, metrics, and conversation dynamics
    • 🔄 Flexible Import: Support for various chat export formats
    • 🚀 MCP Integration: Easy integration with Claude and other MCP-compatible systems

    Quick Start

    # Install the package
    pip install mcp-chat-analysis-server
    
    # Set up configuration
    cp config.example.yml config.yml
    # Edit config.yml with your database settings
    
    # Run the server
    python -m mcp_chat_analysis.server
    

    MCP Integration

    Add to your claude_desktop_config.json:

    {
      "mcpServers": {
        "chat-analysis": {
          "command": "python",
          "args": ["-m", "mcp_chat_analysis.server"],
          "env": {
            "QDRANT_URL": "http://localhost:6333",
            "NEO4J_URL": "bolt://localhost:7687",
            "NEO4J_USER": "neo4j",
            "NEO4J_PASSWORD": "your-password"
          }
        }
      }
    }
    

    Available Tools

    import_conversations

    Import and analyze chat conversations

    {
        "source_path": "/path/to/export.zip",
        "format": "openai_native"  # or html, markdown, json
    }
    

    semantic_search

    Search conversations by semantic similarity

    {
        "query": "machine learning applications",
        "limit": 10,
        "min_score": 0.7
    }
    

    analyze_metrics

    Analyze conversation metrics

    {
        "conversation_id": "conv-123",
        "metrics": [
            "message_frequency",
            "response_times",
            "topic_diversity"
        ]
    }
    

    extract_concepts

    Extract and analyze concepts

    {
        "conversation_id": "conv-123",
        "min_relevance": 0.5,
        "max_concepts": 10
    }
    

    Architecture

    See ARCHITECTURE.md for detailed diagrams and documentation of:

    • System components and interactions
    • Data flow and processing pipeline
    • Storage schema and vector operations
    • Tool integration mechanism

    Prerequisites

    • Python 3.8+
    • Neo4j database for knowledge graph storage
    • Qdrant vector database for semantic search
    • sentence-transformers for embeddings

    Installation

    1. Install the package:
    pip install mcp-chat-analysis-server
    
    1. Set up databases:
    # Using Docker (recommended)
    docker compose up -d
    
    1. Configure the server:
    cp .env.example .env
    # Edit .env with your settings
    

    Development

    1. Clone the repository:
    git clone https://github.com/rebots-online/mcp-chat-analysis-server.git
    cd mcp-chat-analysis-server
    
    1. Install development dependencies:
    pip install -e ".[dev]"
    
    1. Run tests:
    pytest tests/
    

    Contributing

    1. Fork the repository
    2. Create a feature branch
    3. Submit a pull request

    See CONTRIBUTING.md for guidelines.

    License

    MIT License - See LICENSE file for details.

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