DeepMemory FAQs

Question 1

What happens to memory writes if the server is initializing or temporarily unavailable?

Accepted Answer

DeepMemory features a persistent write queue. If the storage backend is busy or initializing, `add_memory` requests are automatically queued and processed once the database is ready, ensuring no memory writes are lost.

Question 2

What database backends does DeepMemory support?

Accepted Answer

By default, DeepMemory uses SQLite for local storage. It also offers optional support for MySQL, which can be enabled and configured via CLI flags or environment variables during server startup.

Question 3

How does DeepMemory help organize complex information for AI agents?

Accepted Answer

DeepMemory includes a powerful clustering mechanism. This allows you to group structured details related to a subject and link associated memories, making it easier to manage and retrieve complex, interconnected information.

Question 4

Can DeepMemory store different types of information, not just conversational memories?

Accepted Answer

Yes, DeepMemory offers dedicated storage and tools for managing development-related documents ('docs'). This separate storage ensures that development information is kept distinct from user memories, allowing for specialized management and retrieval.

Question 5

What is DeepMemory and what is its primary function?

Accepted Answer

DeepMemory is a Model Context Protocol (MCP) server designed to provide robust, long-term memory storage for conversational agents, allowing them to retain and access information over time for more coherent interactions.

DeepMemory

DeepMemory

Key Features

Use Cases

Key Features

Use Cases