Memory Layer FAQs

Question 1

Which APIs and frameworks does Memory Layer support?

Accepted Answer

Memory Layer exposes memory tools over both MCP (Model Context Protocol) and standard REST APIs, making it compatible with leading agent frameworks like Claude, Copilot, Bedrock, LangChain, CrewAI, and AutoGen.

Question 2

Can AI agents manage their own memory within Memory Layer?

Accepted Answer

Yes, agents are empowered to self-curate their memory using the same tool interface, enabling them to decide what information to intake, promote, merge, or expire for optimal relevance and efficiency.

Question 3

How does Memory Layer store and retrieve information?

Accepted Answer

It stores natural-language documents with vector embeddings in MongoDB, leveraging Atlas Vector Search for broad semantic recall and TurboQuant compression for fast, precise retrieval within semantic categories.

Question 4

What is Memory Layer?

Accepted Answer

Memory Layer is a Go MCP server that provides durable, searchable, and self-curating memory for AI agents. It allows agents to store, retain, and recall natural-language information over time.

Question 5

What are the core requirements to run Memory Layer?

Accepted Answer

You need Go 1.22+, MongoDB Atlas 7.0+ with Vector Search indexes, Docker, and an embedding provider (VoyageAI, OpenAI, Ollama, or Bedrock) configured with the respective API keys.

Memory Layer

主要功能

使用案例

Memory Layer

主要功能

使用案例