T1nker 1220 Memories With Lessons MCP Server
T

T1nker 1220 Memories With Lessons MCP Server

An implementation of a persistent memory server based on knowledge graphs, supporting cross - session memory of user information and an error learning system, including core functions such as entity management, relationship establishment, observation recording, and error lessons.
2 points
6.5K

What is Knowledge Graph Memory Server?

This server provides Claude with long - term memory capabilities by storing information in a structured knowledge graph format. It remembers user details, relationships between entities, and lessons learned from past errors to improve future interactions.

How does it work?

The server stores information as entities (nodes) connected by relations (edges) with attached observations (facts). Special 'lesson' entities capture error patterns and solutions for continuous learning.

When should I use it?

Ideal for personalized AI assistants that need to remember user preferences, maintain context across conversations, or learn from troubleshooting experiences.

Key Features

Entity Tracking
Store and organize information about people, organizations, and events as interconnected entities.
Relationship Mapping
Define and visualize how different entities connect and interact with each other.
Error Learning System
Capture error patterns and solutions as lessons that improve over time based on success rates.
Persistent Memory
Maintain information across different chat sessions for continuous context.
Advantages
Personalized interactions through memory of user details
Faster error resolution with learned solutions
Structured knowledge representation enables complex reasoning
Lightweight local storage maintains privacy
Limitations
Requires manual setup for integration
Local storage means memories don't sync across devices
Initial learning curve for optimal prompt engineering

Setup Guide

Installation
Choose your preferred installation method from Docker, NPX, or custom build.
Configuration
Add the server configuration to your claude_desktop_config.json file.
System Prompt
Configure Claude's interaction pattern with the memory system using the provided prompt template.

Usage Scenarios

Personalized Assistant
Remember user preferences across conversations
Technical Troubleshooting
Store and recall solutions to common errors

Frequently Asked Questions

Where is the memory data stored?
How do I clear the memory?
Can I use this with Claude.ai?

Additional Resources

GitHub Repository
Source code and original implementation
Cursor MCP Documentation
Official Model Context Protocol documentation
Knowledge Graphs Explained
Introductory article about knowledge graphs

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "memory": {
      "command": "docker",
      "args": ["run", "-i", "-v", "claude-memory:/app/dist", "--rm", "mcp/memory"]
    }
  }
}

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-memory"
      ]
    }
  }
}

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-memory"
      ],
      "env": {
        "MEMORY_FILE_PATH": "/path/to/custom/memory.json"
      }
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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