Introduction to ai-memory

ai-memory is a memory service tool I developed based on MCP (Model Context Protocol). Simply put, it enables AI to have “memory” capabilities.

Main Features

Semantic Memory Storage

Just give it a piece of text, and it will automatically extract key information and store it as structured memory. No manual organization needed, which is quite convenient.

Multi-dimensional Scopes

It supports three types of scopes: personId, agentId, and sessionId. You can organize memories by person, by AI agent, or by session, offering great flexibility.

Semantic Search

The underlying technology uses vector similarity search, so you don’t need exact keyword matches when searching—semantically similar content can also be found.

CRUD Operations

Create, read, update, and delete operations are all available, meeting basic memory management needs.

Use Cases

This tool is suitable for several types of applications:

• Long-term memory management for AI assistants, allowing them to “remember” previous conversations
• Maintaining context within a single conversation, preventing the AI from forgetting what was said earlier
• Sharing memories between multiple AI agents to enable collaboration