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BytesAgain › Skills › Agent Memory Pro
🦀 ClawHub

Agent Memory Pro

by @aiwithabidi

Full AI agent memory stack — Mem0 unified memory engine with vector search (Qdrant) and knowledge graph (Neo4j), plus SQLite for structured data. Complete se...

Versionv1.0.0
Installs1
#clawhub
⚡ When to Use
TriggerAction
- Managing structured data: projects, contacts, tasks, bookmarks
- Setting up the brain stack after container rebuild
- Batch seeding memory with key facts
💡 Examples

Memory Engine (Mem0 — vectors + graph)

# Store a fact
python3 {baseDir}/scripts/memory_engine.py add "Abidi's business focuses on Voice AI"
Semantic recall

python3 {baseDir}/scripts/memory_engine.py search "what does Abidi's business do"
List all memories

python3 {baseDir}/scripts/memory_engine.py get-all
Test connections (Qdrant, Neo4j, Langfuse)

python3 {baseDir}/scripts/memory_engine.py test

Structured Database (SQLite)

# List tables
python3 {baseDir}/scripts/structured_db.py tables
Insert data

python3 {baseDir}/scripts/structured_db.py insert projects '{"name":"MyProject","status":"active"}'
Query

python3 {baseDir}/scripts/structured_db.py query "SELECT * FROM projects"

Setup & Seeding

# Install Python deps after container rebuild
bash {baseDir}/scripts/setup_brain.sh
Batch seed with key facts

python3 {baseDir}/scripts/seed_mem0.py

View on ClawHub
TERMINAL
clawhub install agent-memory-pro

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