Memory FAQs

Question 1

Does Memory support multiple, isolated AI conversations?

Accepted Answer

Yes, Memory is built to support multiple simultaneous conversations by creating isolated memory spaces for each unique conversation ID. This prevents context leakage between different discussions, ensuring that each AI conversation maintains its own distinct and relevant short-term and long-term memory.

Question 2

How does Memory support Chinese language processing?

Accepted Answer

Memory integrates built-in Chinese language support through jieba segmentation. This optimization ensures accurate keyword extraction and efficient text processing for Chinese messages, making it highly effective for AI models operating in Chinese-speaking environments.

Question 3

What is 'Memory' and how does it benefit AI models?

Accepted Answer

Memory is a Model Context Protocol (MCP) server designed to provide sophisticated short-term and long-term memory management for AI models. It enhances an AI's ability to maintain conversational context, recall relevant information, and process Chinese language effectively, leading to more intelligent and coherent interactions.

Question 4

What kind of long-term memory capabilities does Memory offer?

Accepted Answer

Memory provides trigger-based long-term memory, allowing permanent storage of information with flexible JavaScript activation conditions. These triggers run in a secure, sandboxed environment, enabling AI models to recall specific facts or instructions when relevant contextual cues are met.

Question 5

How does Memory manage short-term context and recall?

Accepted Answer

Short-term memory in Memory is dynamic, keyword-based, and subject to an exponential time-decay model. It uses relevance scoring, smart selection tiers (top, next relevant, and random flashback), and automatic cleanup to ensure AI models always have access to the most pertinent and timely conversational context.

Memory

About

Key Features

Use Cases