Core Functionality
Claude-Mem automatically records agent activities during sessions, creates semantic summaries, and stores them for future use. This system maintains project knowledge continuity even after sessions end or reconnect. The memory persistence works with multiple AI platforms including Claude Code, OpenClaw, and others listed in the project description.
Installation and Integration
The project offers installation options for various environments including Claude Code, OpenCode, T3 Code, and OpenClaw gateways. Users can install through command-line tools or plugin marketplaces, with specific setup instructions for different AI development platforms. The system requires Node.js 20.0.0 or higher and includes automated dependency management.
Search and Context Retrieval
Claude-Mem implements a three-layer search workflow for efficient memory retrieval. The system allows users to search memory indexes, view chronological context around observations, and fetch detailed information for specific entries. This approach reduces token usage by filtering results before retrieving full details.
Technical Architecture
The system uses lifecycle hooks to capture session events, a worker service with HTTP API for local access, and SQLite database for storage. It integrates Chroma vector database for hybrid semantic and keyword search capabilities. The architecture supports both local and cloud-based memory management with privacy controls.
Our take
Claude-Mem provides persistent memory solutions for AI agents, enabling continuous context retention across sessions through automated observation capture and efficient search capabilities.