Persistent memory for AI agents to store facts, learn from actions, recall information, and track entities across sessions.
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Persistent memory system for AI agents. Remember facts, learn from experience, and track entities across sessions.
clawdhub install agent-memory
from src.memory import AgentMemorymem = AgentMemory()
Remember facts
mem.remember("Important information", tags=["category"])
Learn from experience
mem.learn( action="What was done", context="situation", outcome="positive", # or "negative" insight="What was learned" )
Recall memories
facts = mem.recall("search query") lessons = mem.get_lessons(context="topic")
Track entities
mem.track_entity("Name", "person", {"role": "engineer"})
Add to your AGENTS.md or HEARTBEAT.md:
## Memory ProtocolOn session start:
- Load recent lessons:
mem.get_lessons(limit=5)- Check entity context for current task
- Recall relevant facts
On session end:
- Extract durable facts from conversation
- Record any lessons learned
Update entity information
Default:
~/.agent-memory/memory.dbCustom:
AgentMemory(db_path="/path/to/memory.db")No automatic installation available. Please visit the source repository for installation instructions.
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