Claude Memory MCP Server
Provides a tiered, persistent memory architecture for Claude to automatically capture and retrieve user preferences, facts, and conversation history across sessions. It supports semantic search and seamless integration with the Claude desktop application using the Model Context Protocol.
README
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
-
Prerequisites:
- Python 3.8-3.12
- pip package manager
-
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 -
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.
-
Automatic Memory: Claude will automatically:
- Remember important details you share
- Store user preferences and facts
- Recall relevant information when needed
-
Memory Recall: To see what Claude remembers, simply ask:
- "What do you remember about me?"
- "What do you know about my preferences?"
-
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
Examples
The examples directory contains scripts demonstrating how to interact with the Memory MCP Server:
store_memory_example.py: Example of storing a memoryretrieve_memory_example.py: Example of retrieving memories
Troubleshooting
If you encounter issues:
- Check the Compatibility Guide 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 - see the LICENSE file for details.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。