Claude Memory MCP Server
A persistent memory server for Large Language Models, designed to integrate with the Claude desktop application. It supports tiered memory, semantic search, and automatic memory management.
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.
Máy chủ liên quan
Scout Monitoring MCP
nhà tài trợPut performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
nhà tài trợAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
cratesio-mcp
MCP server for querying crates.io - the Rust package registry
Ebitengine MCP
A server for Ebitengine games that provides debugging and recording tools by capturing game state.
Zyla API Hub MCP Server
Connect any AI agent to 7,500+ APIs on the Zyla API Hub using a single MCP tool (call_api)
Together AI Image Server
A TypeScript-based server for generating images using the Together AI API.
DevContainer MCP Server
Manage DevContainer environments using natural language prompts in any MCP-compatible editor.
mcp-graphql
A GraphQL server that supports the Model Context Protocol (MCP), enabling Large Language Models (LLMs) to interact with GraphQL APIs through schema introspection and query execution.
SAME (Stateless Agent Memory Engine
Your AI's memory shouldn't live on someone else's server — 12 MCP tools that give it persistent context from your local markdown, no cloud, no API keys, single binary.
ShaderToy-MCP
Query and interact with ShaderToy shaders using large language models.
Frame0 MCP Server
Create and modify wireframes in the Frame0 app through natural language prompts.
JSONPlaceholder
A free public REST API for testing and prototyping, powered by JSONPlaceholder.