AgentDB Memory Patterns
If you're building AI agents that need to remember things between sessions, this gives you memory management patterns on top of AgentDB's persistent storage. It hooks into ReasoningBank so your agents can recall past conversations and maintain context without you reinventing the wheel. The performance claims are aggressive (150x to 12,500x faster than traditional solutions), though without seeing implementation details it's hard to verify. Worth checking out if you're already in the AgentDB ecosystem or need a quick way to add memory to conversational agents. Requires Node.js 18+ and AgentDB v1.0.7 or higher.
- GitHub stars
- 67.2K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add ruvnet/ruflo --skill 'AgentDB Memory Patterns' --agent claude-codeInstalls into .claude/skills of the current project.
Files
AgentDB Memory Patterns
What This Skill Does
Provides memory management patterns for AI agents using AgentDB's persistent storage and ReasoningBank integration. Enables agents to remember conversations, learn from interactions, and maintain context across sessions.
Performance: 150x-12,500x faster than traditional solutions with 100% backward compatibility.
Prerequisites
- Node.js 18+
- AgentDB v1.0.7+ (via agentic-flow or standalone)
- Understanding of agent architectures
Quick Start with CLI
Initialize AgentDB
# Initialize vector database
npx agentdb@latest init .$agents.db
# Or with custom dimensions
npx agentdb@latest init .$agents.db --dimension 768
# Use preset configurations
npx agentdb@latest init .$agents.db --preset large
# In-memory database for testing
npx agentdb@latest init .$memory.db --in-memory
Start MCP Server for Claude Code
# Start MCP server (integrates with Claude Code)
npx agentdb@latest mcp
# Add to Claude Code (one-time setup)
claude mcp add agentdb npx agentdb@latest mcp
Create Learning Plugin
# Interactive plugin wizard
npx agentdb@latest create-plugin
Sponsors
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- Repository
- github.com/ruvnet/ruflo
- First seen
- Jun 3, 2026
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