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
MCP Integration
Add to your
claude_desktop_config.json:Available Tools
import_conversations
Import and analyze chat conversations
semantic_search
Search conversations by semantic similarity
analyze_metrics
Analyze conversation metrics
extract_concepts
Extract and analyze concepts
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
- Install the package:
- Set up databases:
- Configure the server:
Development
- Clone the repository:
- Install development dependencies:
- Run tests:
Contributing
- Fork the repository
- Create a feature branch
- Submit a pull request
See CONTRIBUTING.md for guidelines.
License
MIT License - See LICENSE file for details.
Related Projects
Support
- Documentation
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
MCP Integration
Add to your
claude_desktop_config.json:Available Tools
import_conversations
Import and analyze chat conversations
semantic_search
Search conversations by semantic similarity
analyze_metrics
Analyze conversation metrics
extract_concepts
Extract and analyze concepts
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
- Install the package:
- Set up databases:
- Configure the server:
Development
- Clone the repository:
- Install development dependencies:
- Run tests:
Contributing
- Fork the repository
- Create a feature branch
- Submit a pull request
See CONTRIBUTING.md for guidelines.
License
MIT License - See LICENSE file for details.
Related Projects
Support
- Documentation