I built a persistent memory MCP with Hebbian learning and GraphRAG

Leandro Pérez González — Sun, 08 Mar 2026 18:14:36 +0000

The Problem

AI coding assistants forget everything between sessions. Every conversation starts from zero. You explain your architecture, your patterns, your preferences — and next time, it's gone.
I built Cuba-Memorys to fix this.

What is it?

An MCP server that gives AI agents persistent long-term memory using a knowledge graph backed by PostgreSQL. 12 tools with Cuban-themed names.

Key Features

🧠 Knowledge Graph

Entities, observations, and typed relations that persist across sessions. Your AI remembers projects, decisions, patterns, and connections between them.

⚡ Hebbian Learning

"Neurons that fire together wire together" — memories strengthen with use (Oja's rule) and fade adaptively using FSRS spaced repetition (the algorithm behind Anki).

🔍 4-Signal RRF Fusion Search

Not just keyword matching. Cuba-Memorys fuses 4 search signals:

TF-IDF similarity
PostgreSQL full-text search
Trigram matching
Optional pgvector HNSW embeddings Results are ranked using Reciprocal Rank Fusion for maximum recall. ### 🕸️ GraphRAG Enrichment Top search results are automatically enriched with degree-1 graph neighbors, giving your AI topological context — not just text matches. ### 🛡️ Anti-Hallucination Grounding Verify claims against stored knowledge with graduated confidence scoring: verified → partial → weak → unknown. Your AI can fact-check itself before answering. ### 😴 REM Sleep Consolidation After 15 minutes of inactivity, the system automatically runs maintenance: adaptive decay, deduplication, and memory consolidation. Like biological sleep for your AI's memory. ### 📊 Graph Analytics
PageRank — Find the most important entities
Louvain communities — Discover knowledge clusters
Betweenness centrality — Identify bridge concepts ## The 12 Tools | Tool | Purpose | |------|---------| | cuba_alma | CRUD knowledge graph entities | | cuba_cronica | Attach observations to entities | | cuba_puente | Create/traverse relations | | cuba_faro | Search with anti-hallucination | | cuba_alarma | Report and track errors | | cuba_expediente | Search past errors (anti-repetition) | | cuba_remedio | Mark errors as resolved | | cuba_eco | RLHF feedback loop | | cuba_decreto | Record architecture decisions | | cuba_jornada | Session management | | cuba_vigia | Graph analytics | | cuba_zafra | Memory maintenance | ## Quick Start


json
{
  "mcpServers": {
    "cuba-memorys": {
      "command": "python",
      "args": ["-m", "cuba_memorys"],
      "env": {
        "DATABASE_URL": "postgresql://user:pass@localhost:5432/brain"
      }
    }
  }
}
¨¨


The database auto-provisions via Docker if needed. Zero manual setup.

Why "Cuba"?
The tools are named after Cuban Spanish words — alma (soul), crónica (chronicle), faro (lighthouse), remedio (remedy). It started as a personal project and the naming stuck.

Links
GitHub: github.com/lENADRO1910/cuba-memorys
PyPI: pip install cuba-memorys
License: CC BY-NC 4.0
If you find it useful, a ⭐ on GitHub would mean a lot. Open to feedback and contributions!