Semantic Memory FAQs

Question 1

Can I manage multiple semantic knowledge stores with this tool?

Accepted Answer

Yes, Semantic Memory supports federated routing across multiple disk-native RWIF semantic stores. You can configure each store with explicit read-only or read-write access modes, allowing for flexible and governed access to diverse knowledge bases.

Question 2

What are MCP tools and their capabilities?

Accepted Answer

MCP (Memory Control Plane) tools are command-line utilities provided by Semantic Memory for various operations. These include semantic querying, answering, reasoning, store management, and governed write workflows for explicit control over memory mutations.

Question 3

What are the deployment options for Semantic Memory?

Accepted Answer

Semantic Memory offers flexible deployment options, including ready-to-use examples for Docker, Docker Compose, and Docker Desktop. This enables easy integration and scalability across different environments.

Question 4

How does Semantic Memory replace traditional vector databases?

Accepted Answer

It transforms semantic retrieval from a 'cluster-and-index problem' to a 'file-and-router problem.' By using compact, portable RWIF files on normal filesystems, it removes the need for a separate database platform, saving RAM/VRAM resources and simplifying storage management.

Question 5

What is Semantic Memory and how does it work?

Accepted Answer

Semantic Memory provides a server that exposes disk-native semantic memory using RWIF (Resonant Wave Information Format) files. This allows AI models and agents to retrieve grounded semantic evidence directly from disk, eliminating the need for a heavyweight, resident vector database.

Semantic Memory

Semantic Memory

Key Features

Use Cases

Key Features

Use Cases