npx mcpbar@latest install WhenMoon-afk/claude-memory-mcp -c claude

npx mcpbar@latest edit -c claude

{
  "mcpServers": {
    "Memory Server": {
      "command": "python",
      "args": [
        "-m",
        "memory_mcp"
      ],
      "env": {
        "MEMORY_FILE_PATH": "/path/to/your/memory.json"
      }
    }
  }
}

Claude Memory MCP Server

An MCP (Model Context Protocol) server implementation that provides persistent memory capabilities for Large Language Models, specifically designed to integrate with the Claude desktop application.

Overview

This project implements optimal memory techniques based on comprehensive research of current approaches in the field. It provides 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

Quick Start

Option 1: Using Docker (Recommended)

# Clone the repository
git clone https://github.com/WhenMoon-afk/claude-memory-mcp.git
cd claude-memory-mcp

# Start with Docker Compose
docker-compose up -d

Configure Claude Desktop to use the containerized MCP server (see Docker Usage Guide for details).

Option 2: Standard Installation

1. Prerequisites:

   • Python 3.8-3.12
   • pip package manager

2. Installation:

   # Clone the repository
   git clone https://github.com/WhenMoon-afk/claude-memory-mcp.git
   cd claude-memory-mcp
   
   # Install dependencies
   pip install -r requirements.txt
   
   # Run setup script
   chmod +x setup.sh
   ./setup.sh
   

3. Claude Desktop Integration:

   Add the following to your Claude configuration file:

   {
     "mcpServers": {
       "memory": {
         "command": "python",
         "args": ["-m", "memory_mcp"],
         "env": {
           "MEMORY_FILE_PATH": "/path/to/your/memory.json"
         }
       }
     }
   }
   

Using Memory with Claude

The Memory MCP Server enables Claude to remember information across conversations without requiring explicit commands.

1. Automatic Memory: Claude will automatically:

   • Remember important details you share
   • Store user preferences and facts
   • Recall relevant information when needed

2. Memory Recall: To see what Claude remembers, simply ask:

   • "What do you remember about me?"
   • "What do you know about my preferences?"

3. System Prompt: For optimal memory usage, add this to your Claude system prompt:

   This Claude instance has been enhanced with persistent memory capabilities.
   Claude will automatically remember important details about you across
   conversations and recall them when relevant, without needing explicit commands.
   

See the User Guide for detailed usage instructions and examples.

Documentation

• User Guide
• Docker Usage Guide
• Compatibility Guide
• Architecture
• Claude Integration Guide

Examples

The examples directory contains scripts demonstrating how to interact with the Memory MCP Server:

• store_memory_example.py: Example of storing a memory
• retrieve_memory_example.py: Example of retrieving memories

Troubleshooting

If you encounter issues:

1. Check the Compatibility Guide for dependency requirements
2. Ensure your Python version is 3.8-3.12
3. For NumPy issues, use: pip install "numpy>=1.20.0,<2.0.0"
4. 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 - see the LICENSE file for details.