brain-v3-skillClaw Brain - Personal AI Memory System for OpenClaw/ClawDBot. Provides memory, personality, bonding, and learning capabilities with encrypted secrets support. Auto-refreshes on service restart.
Install via ClawdBot CLI:
clawdbot install clawcolab/brain-v3-skillPersonal AI Memory System with Soul, Bonding, and Learning for OpenClaw/ClawDBot.
Auto-Refresh on Restart: ClawBrain automatically refreshes memory when the service restarts.
# Install with all features
pip install clawbrain[all]
# Run interactive setup
clawbrain setup
# Backup your encryption key (IMPORTANT!)
clawbrain backup-key --all
# Restart your service
sudo systemctl restart clawdbot # or openclawThe setup command will:
# Clone to your skills directory
cd ~/.openclaw/skills # or ~/clawd/skills or ~/.clawdbot/skills
git clone https://github.com/clawcolab/clawbrain.git
cd clawbrain
pip install -e .[all]
clawbrain setupAfter installation, optionally configure your agent ID:
# Create systemd drop-in config
sudo mkdir -p /etc/systemd/system/clawdbot.service.d # or openclaw.service.d
sudo tee /etc/systemd/system/clawdbot.service.d/brain.conf << EOF
[Service]
Environment="BRAIN_AGENT_ID=your-agent-name"
# Optional: PostgreSQL (for production)
# Environment="BRAIN_POSTGRES_HOST=localhost"
# Environment="BRAIN_POSTGRES_PASSWORD=your-password"
# Optional: Redis (for caching)
# Environment="BRAIN_REDIS_HOST=localhost"
EOF
sudo systemctl daemon-reload
sudo systemctl restart clawdbot # or openclaw| Variable | Description | Default |
|----------|-------------|---------|
| BRAIN_AGENT_ID | Unique ID for this agent's memories | default |
| BRAIN_ENCRYPTION_KEY | Fernet key for encrypting sensitive data (auto-generated if not set) | - |
| BRAIN_POSTGRES_HOST | PostgreSQL host | localhost |
| BRAIN_POSTGRES_PASSWORD | PostgreSQL password | - |
| BRAIN_POSTGRES_PORT | PostgreSQL port | 5432 |
| BRAIN_POSTGRES_DB | PostgreSQL database | brain_db |
| BRAIN_POSTGRES_USER | PostgreSQL user | brain_user |
| BRAIN_REDIS_HOST | Redis host | localhost |
| BRAIN_REDIS_PORT | Redis port | 6379 |
| BRAIN_STORAGE | Force storage: sqlite, postgresql, auto | auto |
gateway:startup eventBRAIN_AGENT_ID/new Commandcommand:new event ClawBrain supports encrypting sensitive data like API keys and credentials.
Setup:
# Run setup to generate encryption key
clawbrain setup
# Backup your key (IMPORTANT!)
clawbrain backup-key --allUsage:
# Store encrypted secret
brain.remember(
agent_id="assistant",
memory_type="secret", # Memory type 'secret' triggers encryption
content="sk-1234567890abcdef",
key="openai_api_key"
)
# Retrieve and automatically decrypt
secrets = brain.recall(agent_id="assistant", memory_type="secret")
api_key = secrets[0].content # Automatically decryptedKey Management CLI:
clawbrain show-key # View key info (masked)
clawbrain show-key --full # View full key
clawbrain backup-key --all # Backup with all methods
clawbrain generate-key # Generate new keyā ļø Important: Backup your encryption key! Lost keys = lost encrypted data.
ClawBrain includes a command-line interface:
| Command | Description |
|---------|-------------|
| clawbrain setup | Set up ClawBrain, generate key, install hooks |
| clawbrain generate-key | Generate new encryption key |
| clawbrain show-key | Display current encryption key |
| clawbrain backup-key | Backup key (file, QR, clipboard) |
| clawbrain health | Check health status |
| clawbrain info | Show installation info |
| Event | Action |
|-------|--------|
| gateway:startup | Initialize brain, refresh memories |
| command:new | Save session to memory |
For development or manual installation:
# Clone to your skills directory
cd ~/.openclaw/skills # or ~/clawd/skills or ~/.clawdbot/skills
git clone https://github.com/clawcolab/clawbrain.git
cd clawbrain
./install.shFor direct Python usage (outside ClawdBot/OpenClaw):
from clawbrain import Brain
brain = Brain()| Method | Description | Returns |
|--------|-------------|---------|
| get_full_context() | Get all context for personalized responses | dict |
| remember() | Store a memory | None |
| recall() | Retrieve memories | List[Memory] |
| learn_user_preference() | Learn user preferences | None |
| get_user_profile() | Get user profile | UserProfile |
| detect_user_mood() | Detect current mood | dict |
| detect_user_intent() | Detect message intent | str |
| generate_personality_prompt() | Generate personality guidance | str |
| health_check() | Check backend connections | dict |
| close() | Close connections | None |
context = brain.get_full_context(
session_key="telegram_12345", # Unique session ID
user_id="username", # User identifier
agent_id="assistant", # Bot identifier
message="Hey, how's it going?" # Current message
)Returns:
{
"user_profile": {...}, # User preferences, interests
"mood": {"mood": "happy", ...}, # Current mood
"intent": "question", # Detected intent
"memories": [...], # Relevant memories
"personality": "...", # Personality guidance
"suggested_responses": [...] # Response suggestions
}mood = brain.detect_user_mood("I'm so excited about this!")
# Returns: {"mood": "happy", "confidence": 0.9, "emotions": ["joy", "anticipation"]}intent = brain.detect_user_intent("How does AI work?")
# Returns: "question"
intent = brain.detect_user_intent("Set a reminder for 3pm")
# Returns: "command"
intent = brain.detect_user_intent("I had a great day today")
# Returns: "casual"import sys
sys.path.insert(0, "ClawBrain")
from clawbrain import Brain
class AssistantBot:
def __init__(self):
self.brain = Brain()
def handle_message(self, message, chat_id):
# Get context
context = self.brain.get_full_context(
session_key=f"telegram_{chat_id}",
user_id=str(chat_id),
agent_id="assistant",
message=message
)
# Generate response using context
response = self.generate_response(context)
# Learn from interaction
self.brain.learn_user_preference(
user_id=str(chat_id),
pref_type="interest",
value="AI"
)
return response
def generate_response(self, context):
# Use user preferences
name = context["user_profile"].name or "there"
mood = context["mood"]["mood"]
# Personalized response
if mood == "frustrated":
return f"Hey {name}, I'm here to help. Let me assist you."
else:
return f"Hi {name}! How can I help you today?"
def shutdown(self):
self.brain.close()No configuration needed. Data stored in local SQLite database.
brain = Brain({"storage_backend": "sqlite"})Best for: Development, testing, single-user deployments
Requires PostgreSQL and Redis servers.
brain = Brain() # Auto-detectsRequirements:
psycopg2-binary, redispip install psycopg2-binary redisBest for: Production, multi-user, high-concurrency
clawbrain.py - Main Brain class with all featuresinit.py - Module exportsSKILL.md - This documentationskill.json - ClawdHub metadataREADME.md - Quick start guide# Ensure ClawBrain folder is in your path
sys.path.insert(0, "ClawBrain")# Check environment variables
echo $POSTGRES_HOST
echo $POSTGRES_PORT
# Verify PostgreSQL is running
pg_isready -h $POSTGRES_HOST -p $POSTGRES_PORT# Check Redis is running
redis-cli pingIf PostgreSQL/Redis are unavailable, Claw Brain automatically falls back to SQLite:
brain = Brain({"storage_backend": "sqlite"})Generated Feb 26, 2026
Integrate ClawBrain into a customer support chatbot to remember user preferences and past issues, enabling personalized responses and reducing repetition. It tracks conversation context and mood to adapt tone, improving customer satisfaction and efficiency.
Use ClawBrain in a mental health app to build a bonding relationship with users, learning their emotional patterns and providing empathetic, consistent support. It stores encrypted session summaries securely, aiding in continuity of care and personalized therapy sessions.
Deploy ClawBrain in an educational AI tutor to track student progress, learning styles, and interests, tailoring lessons and feedback. It evolves traits like curiosity and helpfulness to engage students and improve retention over time.
Incorporate ClawBrain into a smart home assistant to remember user routines, preferences for lighting or temperature, and past commands for context-aware automation. It auto-refreshes on restart, ensuring reliable memory persistence across sessions.
Implement ClawBrain in a sales chatbot to learn customer interests and communication styles, enabling personalized product recommendations and follow-ups. It uses encrypted secrets to securely store API keys for CRM integrations, enhancing lead conversion.
Offer ClawBrain as a SaaS for businesses, charging monthly fees for personalized AI memory features, encrypted storage, and support. Revenue comes from tiered plans based on memory capacity and advanced traits like creativity or empathy.
Provide a free version with basic memory and SQLite storage, then upsell to paid tiers for PostgreSQL integration, encrypted secrets, and advanced analytics. Revenue is generated from upgrades and enterprise customizations.
License ClawBrain's technology to other AI developers or companies, allowing integration into their own products. Revenue comes from one-time licensing fees or royalties based on usage, with support for custom deployments.
š¬ Integration Tip
Ensure the encryption key is backed up securely before deployment to prevent data loss, and configure environment variables like BRAIN_AGENT_ID for multi-agent setups.
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