Agent Memory Store

Shared semantic memory store for AI agents. Store, search, and retrieve memories across agents with TTL decay. SQLite persistence — survives restarts.

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Last updated: April 23, 2026

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Quick Start

Manual Installation

No automatic installation available. Please visit the source repository for installation instructions.

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Agent Memory Store

Cross-agent semantic memory with TTL decay. SQLite-backed — data survives restarts.

Start

python3 scripts/memory_store.py
# Runs on port 8768, DB: /root/.openclaw/workspace/data/agent_memory.db

Quick Start

# Store a memory
curl -X POST http://localhost:8768/memories \
  -H "Content-Type: application/json" \
  -d '{"owner":"my-agent","content":"user prefers SOL payments","ttl_seconds":86400,"public":false}'
Search memories
curl "http://localhost:8768/memories?q=payment+preferences&amp;agent=my-agent"
List all (with agent filter)
curl "http://localhost:8768/memories?agent=my-agent&amp;limit=20"

Endpoints

Method	Path	Description
GET	/health	status + memory count
POST	/memories	store memory `{owner, content, tags?, ttl_seconds?, public?}`
GET	/memories?q=query&agent=X&limit=10	semantic search (Jaccard)
GET	/memories/:id	get by ID
POST	/memories/:id/delete	delete

Changelog

v1.1.0

SQLite persistence (data survives restarts)
Thread-safe writes

DB stored at

/root/.openclaw/workspace/data/agent_memory.db

v1.0.0

Initial release: in-memory store, TTL, cross-agent sharing, Jaccard search

Install

clawhub install agent-memory-store

Agent Memory Store

AI Skill Market Insights

Quick Start

Manual Installation

TEAR & SHARE

Tags

Multi-Agent Patterns

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Agent Memory Store

Start

Quick Start

Search memories

List all (with agent filter)

Endpoints

Changelog

v1.1.0

v1.0.0

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Memory Systems Design

Context Degradation Detection

Context Optimization

Tool Design for Agents

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