AutoMem MCP: Give Your AI Perfect Memory
One command. Infinite memory. Perfect recall across all your AI tools.
npx @verygoodplugins/mcp-automem setup
Your AI assistant now remembers everything. Forever. Across every conversation.
Works with Claude Desktop, Cursor IDE, Claude Code, GitHub Copilot (coding agent), ChatGPT, ElevenLabs, OpenAI Codex - any MCP-compatible AI platform.
The Problem We Solve
Every AI conversation starts from zero. Claude forgets your coding style. Cursor can't learn your patterns. Your assistant doesn't remember yesterday's decisions.
Until now.
AutoMem MCP connects your AI to persistent memory powered by AutoMem - a graph-vector memory service.
What You Get
🧠 Persistent Memory Across Sessions
- AI remembers decisions, patterns, and context forever
- Works across all MCP platforms - Claude Desktop, Cursor, Claude Code
- Cross-device sync - same memory on Mac, Windows, Linux
🏆 Graph-Vector Architecture
- 11 public authorable relationship types between memories (recall results may also include read-only system/internal relations that are not valid
associate_memoriesinputs) - Research-validated approach (HippoRAG 2: 7% better associative memory)
- Sub-second retrieval even with millions of memories
🚀 Works Everywhere You Code
| Platform | Support | Setup Time |
|---|---|---|
| Claude Desktop | ✅ Full | 30 seconds |
| Cursor IDE | ✅ Full | 30 seconds |
| Claude Code | ✅ Full | 30 seconds |
| GitHub Copilot | ✅ Full | 2 minutes |
| OpenAI Codex | ✅ Full | 30 seconds |
| Any MCP client | ✅ Full | 30 seconds |
See It In Action
Claude Desktop with Custom Instructions
Claude automatically recalls memories at conversation start using custom instructions
Cursor IDE with Memory Rules
Cursor uses automem.mdc rule to automatically recall and store memories
Claude Code with Session Memory
Git commits, builds, and deployments automatically stored to memory
OpenAI Codex with Memory Rules
OpenAI Codex uses config.toml to automatically recall and store memories
Your AI Learns Your Code Style
// After 1 week, your AI writes EXACTLY like you
// ✅ It knows you prefer early returns
// ✅ It uses your specific variable naming
// ✅ It matches your comment style
// ✅ It follows YOUR patterns, not generic best practices
Decisions That Feel Like Yours
User: "Should we use Redis for this?"
Without AutoMem:
"Consider RabbitMQ, Kafka, or AWS SQS based on your needs..."
With AutoMem:
"Based on your pattern of preferring boring technology that works,
and your positive experience with Redis in Project X (March 2024),
yes. You specifically value operational simplicity over feature
richness - Redis fits perfectly."
Quick Start
1. Set Up AutoMem Service
You need a running AutoMem service (the memory backend). Choose one:
Option A: Local Development (fastest, free)
git clone https://github.com/verygoodplugins/automem.git
cd automem
make dev
Service runs at http://localhost:8001 - perfect for single-machine use.
Option B: Railway Cloud (recommended for production)
One-click deploy with $5 free credits. Typical cost: ~$0.50-1/month after trial.
👉 AutoMem Service Installation Guide - Complete setup instructions for local, Railway, Docker, and production deployments.
2. Install MCP Client
Claude Desktop - One-Click Install
Download and double-click to install AutoMem in Claude Desktop: