MCP Memory Server

What is MCP Memory Server? MCP Memory Server is a server designed to implement long-term memory capabilities for AI assistants, utilizing PostgreSQL and pgvector for efficient vector similarity search. How to use MCP Memory Server? To use the MCP Memory Server, set up PostgreSQL with the pgvector extension, install the necessary dependencies, configure environment variables, and start the server. You can then interact with the server through its RESTful API. Key features of MCP Memory Server? PostgreSQL with pgvector for vector similarity search Automatic embedding generation using BERT RESTful API for memory operations Semantic search capabilities Support for various types of memories (learnings, experiences, etc.) Tag-based memory retrieval Confidence scoring for memories Real-time updates via Server-Sent Events (SSE) Use cases of MCP Memory Server? Storing and retrieving AI assistant memories Enhancing AI interactions with contextual memory Implementing personalized user experiences based on past interactions FAQ from MCP Memory Server? What is the purpose of the MCP Memory Server? It provides long-term memory capabilities for AI assistants, allowing them to remember past interactions and improve user experience. Is there a specific database requirement? Yes, it requires PostgreSQL 14+ with the pgvector extension installed. How can I check the server status? You can check the server status by visiting http://localhost:3333/mcp/v1/health.

As an MCP (Model Context Protocol) server, MCP 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 the MCP Memory Server, set up PostgreSQL with the pgvector extension, install the necessary dependencies, configure environment variables, and start the server. You can then interact with the server through its RESTful API. Key features of MCP Memory Server? PostgreSQL with pgvector for vector similarity search Automatic embedding generation using BERT RESTful API for memory operations Semantic search capabilities Support for various types of memories (learnings, experiences, etc.) Tag-based memory retrieval Confidence scoring for memories Real-time updates via Server-Sent Events (SSE) Use cases of MCP Memory Server? Storing and retrieving AI assistant memories Enhancing AI interactions with contextual memory Implementing personalized user experiences based on past interactions FAQ from MCP Memory Server? What is the purpose of the MCP Memory Server? It provides long-term memory capabilities for AI assistants, allowing them to remember past interactions and improve user experience. Is there a specific database requirement? Yes, it requires PostgreSQL 14+ with the pgvector extension installed. How can I check the server status? You can check the server status by visiting http://localhost:3333/mcp/v1/health.

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