Knowledge Graph Memory Server

What is MCP Memory Py? MCP Memory Py is a knowledge graph memory server designed to enable persistent memory for AI models like Claude, allowing them to remember user information across chats. How to use MCP Memory Py? To use MCP Memory Py, set up the server with the provided configuration in your Claude Desktop environment, and interact with it through the defined API endpoints to manage entities, relations, and observations. Key features of MCP Memory Py? Persistent memory storage using a local knowledge graph API for creating and managing entities and relations Ability to add, delete, and search observations Integration with Claude for personalized interactions Use cases of MCP Memory Py? Enhancing AI chatbots with memory capabilities Storing user preferences and behaviors for personalized experiences Managing complex relationships and interactions in AI applications FAQ from MCP Memory Py? Can MCP Memory Py be used with other AI models? While designed for Claude, it can potentially be adapted for other models with similar memory requirements. Is there a limit to the number of entities or observations? The limit depends on the storage capacity of the server and the design of the knowledge graph. How can I test the server? You can run unit tests using the command uv run pytest to ensure functionality.

As an MCP (Model Context Protocol) server, Knowledge Graph Memory Server enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.

To use MCP Memory Py, set up the server with the provided configuration in your Claude Desktop environment, and interact with it through the defined API endpoints to manage entities, relations, and observations. Key features of MCP Memory Py? Persistent memory storage using a local knowledge graph API for creating and managing entities and relations Ability to add, delete, and search observations Integration with Claude for personalized interactions Use cases of MCP Memory Py? Enhancing AI chatbots with memory capabilities Storing user preferences and behaviors for personalized experiences Managing complex relationships and interactions in AI applications FAQ from MCP Memory Py? Can MCP Memory Py be used with other AI models? While designed for Claude, it can potentially be adapted for other models with similar memory requirements. Is there a limit to the number of entities or observations? The limit depends on the storage capacity of the server and the design of the knowledge graph. How can I test the server? You can run unit tests using the command uv run pytest to ensure functionality.

Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.