claude-memory-mcp
10
Claude Memory MCP Server provides persistent memory capabilities for Large Language Models to integrate with the Claude desktop application, using a tiered memory architecture and semantic search for intelligent memory management. It supports both Docker and standard installation, making it versatile and easy to integrate.
Claude Memory MCP Server
Overview
This project implements optimal memory techniques based on comprehensive research in the field, providing a standardized way for Claude to maintain persistent memory across conversations and sessions.
Features
- Tiered Memory Architecture: Short-term, long-term, and archival memory tiers
- Multiple Memory Types: Support for conversations, knowledge, entities, and reflections
- Semantic Search: Retrieve memories based on semantic similarity
- Automatic Memory Management: Intelligent memory capture without explicit commands
- Memory Consolidation: Automatic consolidation of short-term memories into long-term memory
- Memory Management: Importance-based memory retention and forgetting
- Claude Integration: Ready-to-use integration with Claude desktop application
- MCP Protocol Support: Compatible with the Model Context Protocol
- Docker Support: Easy deployment using Docker containers
Documentation
Examples
store_memory_example.py: Example of storing a memoryretrieve_memory_example.py: Example of retrieving memories
Troubleshooting
- Check the for dependency requirements
- Ensure your Python version is 3.8-3.12
- For NumPy issues, use:
pip install "numpy>=1.20.0,<2.0.0" - Try using Docker for simplified deployment
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
This project is licensed under the MIT License.