Claude Memory FAQs

Question 1

What is hybrid search and how does it benefit finding memories?

Accepted Answer

Hybrid search in Claude Memory combines semantic vector search (for conceptual relevance) with full-text search (for keyword matching). Results from both methods are merged using Reciprocal Rank Fusion (RRF), ensuring highly accurate and comprehensive retrieval of relevant memories.

Question 2

Can Claude Memory be used for multiple projects simultaneously?

Accepted Answer

Yes, Claude Memory supports multi-namespace configuration. You can run a single server instance and define different namespaces for various projects, ensuring that each project maintains its isolated and relevant set of memories.

Question 3

How does Claude Memory handle embeddings and does it require API keys?

Accepted Answer

Claude Memory uses the `all-MiniLM-L6-v2` model for offline local embeddings. This means it runs entirely on your machine, does not require any external API keys, and can function without an internet connection for embedding generation.

Question 4

How are memories organized and managed within Claude Memory?

Accepted Answer

Memories are organized into four distinct context layers (Permanent Rules, Session-Start, Task-Specific, Ephemeral), each with configurable token budgets. The tool also features automatic deduplication, content versioning, session management, and maintenance operations like promoting/decaying importance and merging near-duplicates.

Question 5

What is Claude Memory and what problem does it solve?

Accepted Answer

Claude Memory is an MCP server designed to give Claude Code persistent memory and robust context management across development sessions. It solves the problem of AI losing context, allowing Claude Code to recall past information, decisions, and rules, making it more effective and efficient over time.

Claude Memory

Claude Memory

Key Features

Use Cases

Key Features

Use Cases