Memory FAQs

Question 1

What kind of operations can I perform with Memory?

Accepted Answer

Memory offers a comprehensive API for all common memory operations, including adding new memories with embeddings, semantic searching, listing, retrieving by ID, updating content or tags, and deleting memories.

Question 2

What is Memory and what problem does it solve?

Accepted Answer

Memory is an MCP Server designed to provide robust long-term memory capabilities for AI agents. It solves the challenge of storing, retrieving, and managing agent memories efficiently by leveraging AWS cloud services for semantic search and metadata management.

Question 3

Which AWS services does Memory integrate with?

Accepted Answer

Memory integrates with AWS S3 Vectors for high-performance vector similarity search, AWS DynamoDB for metadata and ledger management, and AWS Bedrock (specifically Titan Embeddings V2) for generating content embeddings.

Question 4

Is Memory suitable for AI agent development?

Accepted Answer

Yes, Memory is specifically built to enhance AI agents with long-term memory capabilities. It allows agents to store experiences, knowledge, and context, and semantically retrieve them as needed, making interactions more informed and continuous.

Question 5

How does Memory rank search results?

Accepted Answer

Search results are ranked using an advanced scoring algorithm. This algorithm combines semantic similarity with factors like creation age (decay), access count (boost), and last accessed age (decay) to provide highly relevant and contextually rich results.

Memory

Memory

Key Features

Use Cases

Key Features

Use Cases