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2025-03-26

Una implementación del servidor MCP que proporciona capacidades de memoria persistentes para Claude, basada en la investigación sobre técnicas de memoria óptimas de LLM

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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
  • 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

Architecture

The MCP server follows a functional domain-based architecture with the following components:

┌─────────────────────────────────────────────────────────┐
│                   Claude Desktop                        │
└───────────────────────────┬─────────────────────────────┘
                            │
┌───────────────────────────▼─────────────────────────────┐
│                     MCP Interface                       │
│  ┌─────────────────┐  ┌─────────────────┐  ┌──────────┐ │
│  │ Tool Definitions│  │ Request Handler │  │ Security │ │
│  └─────────────────┘  └─────────────────┘  └──────────┘ │
└───────────────────────────┬─────────────────────────────┘
                            │
┌───────────────────────────▼─────────────────────────────┐
│                Memory Domain Manager                    │
├─────────────────┬─────────────────┬────────────────────┤
│  Episodic Domain│  Semantic Domain│  Temporal Domain   │
├─────────────────┴─────────────────┴────────────────────┤
│                  Persistence Domain                    │
└─────────────────────────────────────────────────────────┘

Functional Domains

  1. Episodic Domain: Manages session-based interactions and contextual memory
  2. Semantic Domain: Handles knowledge organization and retrieval
  3. Temporal Domain: Controls time-aware processing of memories
  4. Persistence Domain: Manages storage optimization and retrieval

Installation

Prerequisites

  • Python 3.8 or higher
  • pip package manager

Installation Steps

  1. Clone the repository:

    git clone https://github.com/WhenMoon-afk/claude-memory-mcp.git
    cd claude-memory-mcp
    
  2. Install dependencies:

    pip install -e .
    
  3. Run the setup script:

    chmod +x setup.sh
    ./setup.sh
    

Claude Desktop Integration

To integrate with the Claude desktop application, 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"
      }
    }
  }
}

Memory File Structure

The memory system uses a JSON-based file structure with the following components:

{
  "metadata": {
    "version": "1.0",
    "created_at": "ISO-8601 timestamp",
    "updated_at": "ISO-8601 timestamp"
  },
  "memory_index": {
    // Vector index for fast semantic search
  },
  "short_term_memory": [
    // Recent and frequently accessed memories
  ],
  "long_term_memory": [
    // Older or less frequently accessed memories
  ],
  "archived_memory": [
    // Rarely accessed but potentially valuable memories
  ],
  "memory_schema": {
    // Schema definitions for memory entries
  },
  "config": {
    // Configuration settings for memory management
  }
}

Usage

Starting the Server

python -m memory_mcp

Available Tools

  • store_memory: Store new information in memory
  • retrieve_memory: Retrieve relevant memories based on query
  • list_memories: List available memories with filtering options
  • update_memory: Update existing memory entries
  • delete_memory: Remove specific memories
  • memory_stats: Get statistics about the memory store

Development

Project Structure

memory_mcp/
├── memory/
│   ├── models.py         # Memory data models
│   ├── storage.py        # Memory storage operations
│   ├── retrieval.py      # Memory retrieval operations
│   └── consolidation.py  # Memory consolidation operations
├── domains/
│   ├── episodic.py       # Episodic memory domain
│   ├── semantic.py       # Semantic knowledge domain
│   ├── temporal.py       # Temporal processing domain
│   └── persistence.py    # Storage and retrieval domain
├── mcp/
│   ├── server.py         # MCP server implementation
│   ├── tools.py          # MCP tool definitions
│   └── handler.py        # Request handling
├── security/
│   └── validation.py     # Input validation
└── utils/
    ├── embeddings.py     # Vector embedding utilities
    └── schema.py         # Schema validation

Running Tests

pytest

Research Background

This implementation is based on comprehensive research of current LLM persistent memory techniques:

  • OS-Inspired Memory Management: Tiered memory architecture similar to MemGPT
  • Biological-Inspired Episodic Memory: Context-sensitive memory retrieval
  • Vector Embeddings: Semantic search inspired by vector database approaches
  • Self-Reflection: Memory consolidation through periodic review

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.

Acknowledgements

  • Based on research of optimal memory techniques for LLMs
  • Implements the Model Context Protocol for integration with Claude

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    Reviews

    5 (1)
    Avatar
    user_R8swv0XB
    2025-04-16

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