Cuba-Memorys FAQs

Question 1

What is Cuba-Memorys and what problem does it solve for AI agents?

Accepted Answer

Cuba-Memorys is a Model Context Protocol (MCP) server that provides AI agents with persistent, intelligent long-term memory. It solves the problem of AI agents 'forgetting' information between conversations by maintaining a dynamic knowledge graph and employing advanced memory mechanisms.

Question 2

How does Cuba-Memorys prevent AI hallucinations?

Accepted Answer

It implements robust anti-hallucination grounding through source triangulation and adaptive confidence scoring, verifying claims against stored knowledge and penalizing single-source evidence to ensure factual accuracy.

Question 3

How does Cuba-Memorys enhance information retrieval and recall for AI agents?

Accepted Answer

It features a powerful 4-signal RRF fusion search, KG-neighbor query expansion, and GraphRAG topological enrichment. This ensures high-recall, contextually rich, and session-aware retrieval of relevant information from the knowledge graph.

Question 4

What role does Hebbian learning play in Cuba-Memorys' memory system?

Accepted Answer

Cuba-Memorys uses adaptive Hebbian learning (Oja's rule) combined with FSRS v4 spaced repetition to mimic biological memory. This means frequently accessed memories are strengthened, while less used ones fade adaptively, improving efficiency and relevance.

Question 5

Is Cuba-Memorys difficult to maintain or manage?

Accepted Answer

No, Cuba-Memorys includes an autonomous 'REM Sleep' daemon that handles background memory consolidation, pruning, PageRank recalculation, and other maintenance tasks automatically, requiring zero manual setup for continuous operation.

Cuba-Memorys

Cuba-Memorys

Key Features

Use Cases

Key Features

Use Cases