Memory FAQs

Question 1

What are the main features of the 'Memory' tool?

Accepted Answer

Key features include persistent key-value storage, Namespaces for context separation, Tags for categorization, powerful Full-Text Search, memory access tracking, and usage Statistics to monitor agent knowledge interaction.

Question 2

How does 'Memory' help AI agents remember information?

Accepted Answer

It acts as a persistent knowledge base, storing key-value pairs in a local SQLite database. This allows agents to recall information, past interactions, and critical data long after a conversation session has ended.

Question 3

Is 'Memory' a cloud-based service, or is it self-hosted?

Accepted Answer

'Memory' uses SQLite for zero-configuration, local persistent storage. Data is stored locally on your server, meaning no cloud services, no API keys, and no ongoing costs are involved.

Question 4

Can I organize and search through an agent's stored knowledge?

Accepted Answer

Yes, 'Memory' allows you to organize knowledge using Namespaces for different contexts and Tags for easy filtering. Critically, it features a robust Full-Text Search engine to quickly find relevant information across all stored knowledge.

Question 5

What is 'Memory' for AI Agents?

Accepted Answer

'Memory' is an MCP server designed to provide AI agents with persistent knowledge storage. It enables agents to store, retrieve, and search information across different sessions and tools, preventing context loss.

Memory

Memory

主要功能

使用案例

主要功能

使用案例