AutoMem MCP: Give Your AI Perfect Memory 🧠

⚠️ Beta Notice: The MCP server and AutoMem cloud service are stable and production-ready. However, platform-specific integrations (Cursor hooks, Claude Code automation, etc.) are actively evolving as we optimize based on new LLM capabilities and real-world usage. Expect frequent updates and improvements.

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, ChatGPT, ElevenLabs, Warp Terminal, 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 relationship types between memories (not just similarity)
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	⚠️ Experimental + Auto-capture hooks	1 minute
Warp Terminal	✅ Full + Context-aware	30 seconds
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

Warp Terminal with Memory Rules

Warp Terminal uses memory rules to automatically recall and store context

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

Connect your AI tools to the AutoMem service you just started.

# Guided setup - creates .env and prints config for your AI platform
npx @verygoodplugins/mcp-automem setup

When prompted:

AutoMem Endpoint: http://localhost:8001 (or your Railway URL if deployed)
API Key: Leave blank for local development (or paste your token for Railway)

The wizard will:

✅ Save your endpoint and API key to .env
✅ Generate config snippets for Claude Desktop/Cursor/Code
✅ Validate connection to your AutoMem service

3. Platform-Specific Setup

For Claude Desktop:

# Setup prints config snippet - just paste into claude_desktop_config.json
npx @verygoodplugins/mcp-automem setup

For Cursor IDE:

# Or use CLI to install automem.mdc rule file
npx @verygoodplugins/mcp-automem cursor

Note: After one-click install, configure your AUTOMEM_ENDPOINT in ~/.cursor/mcp.json or Claude Desktop config

For Claude Code:

# Installs automation hooks that capture memories automatically
npx @verygoodplugins/mcp-automem claude-code

For Warp Terminal: See the Warp setup guide and add the MCP configuration from templates/warp/mcp.json to your ~/.warp/mcp.json. Follow usage rules in templates/warp/warp-rules.md.

For OpenAI Codex:

# Add to your Codex MCP configuration
npx @verygoodplugins/mcp-automem config --format=json
 
# Optional: add memory-first rules to this repo
npx @verygoodplugins/mcp-automem codex

👉 Full Installation Guide for detailed MCP client and platform-specific setup

New: Remote MCP over SSE

You can now connect AutoMem to platforms that support MCP over Server‑Sent Events (SSE) via an optional sidecar service (deployable to Railway or any Docker host).

ChatGPT (Developer Mode custom connectors)
Claude.ai (web) and Claude Mobile (iOS/Android)
ElevenLabs Agents Platform

Quick connect URLs (after deploying the sidecar):

ChatGPT, Claude Web/Mobile: https://<your-mcp-domain>/mcp/sse?api_token=<AUTOMEM_API_TOKEN>
ElevenLabs: https://<your-mcp-domain>/mcp/sse with header Authorization: Bearer <AUTOMEM_API_TOKEN>

See the Installation Guide for complete steps and deployment options.

SSE Platforms in Action

ChatGPT Developer Mode: Add your SSE URL as a custom connector

ChatGPT using AutoMem memories via the SSE connector

Claude.ai website connected to AutoMem via remote MCP (SSE)

Claude Mobile (iOS) connected to AutoMem via remote MCP (SSE)

What Happens Next

Timeline	What Your AI Learns
Hour 1	Starts capturing your patterns
Day 1	Learns your decision factors
Day 3	Recognizes your coding style
Week 1	Writes in your voice
Week 2	Makes decisions like you would

Architecture

┌─────────────────────────────────────────────┐
│         Your AI Platforms                   │
│  Claude Desktop │ Cursor │ Claude Code      │
└──────────────┬──────────────────────────────┘
               │ MCP Protocol
               ▼
┌──────────────────────────────────────────────┐
│   @verygoodplugins/mcp-automem (this repo)  │
│   • Translates MCP calls → AutoMem API      │
│   • Platform integrations & rules           │
│   • Handles authentication                   │
└──────────────┬───────────────────────────────┘
               │ HTTP API
               ▼
┌──────────────────────────────────────────────┐
│        AutoMem Service (separate repo)       │
│        github.com/verygoodplugins/automem    │
│   ┌────────────┐      ┌────────────┐        │
│   │  FalkorDB  │      │   Qdrant   │        │
│   │  (Graph)   │      │ (Vectors)  │        │
│   └────────────┘      └────────────┘        │
└──────────────────────────────────────────────┘

This repo (mcp-automem):

MCP client that connects AI platforms to AutoMem
Platform-specific integrations (Cursor rules, Claude Code hooks, etc.)
Setup wizards and configuration tools

AutoMem service:

Backend memory service with graph + vector storage
Deployment guides (local, Railway, Docker, production)
API server with FalkorDB + Qdrant

Features

Core Memory Operations

store_memory - Save memories with content, tags, importance, metadata
recall_memory - Hybrid search (vector + keyword + tags + time)
associate_memories - Create relationships (RELATES_TO, LEADS_TO, etc.)
update_memory - Modify existing memories
delete_memory - Remove memories
check_database_health - Monitor service status

Platform Integrations

Cursor IDE

✅ Memory-first rule file (automem.mdc in .cursor/rules/)
✅ Automatic memory recall at conversation start
✅ Auto-detects project context (package.json, git remote)
✅ Global user rules option for all projects
✅ Simple setup via CLI or one-click install

Claude Code

✅ Automatic session capture (git commits, builds, tests, deploys)
✅ Queue-based processing with deduplication (non-blocking)
✅ Smart filtering (skips trivial files, lock files, build artifacts)
✅ Configurable profiles (lean/extras)
✅ Relationship tracking between memories
✅ Efficient defaults (~1-2 captures/session, high signal-to-noise)

Claude Desktop

✅ Direct MCP integration
✅ Manual and automated workflows
✅ Full memory API access

Warp Terminal

✅ Project context auto-detection
✅ Memory-first terminal assistance
✅ Smart recall on directory changes
✅ Command history with context

Why AutoMem MCP?

vs. Building Your Own

✅ 2 years of R&D already done
✅ Research-validated architecture (HippoRAG 2, MELODI, A-MEM)
✅ Working integrations across all MCP platforms
✅ Active development and community

vs. Other Memory Solutions

✅ True graph relationships (not just vector similarity)
✅ Universal MCP compatibility (works with any MCP client)
✅ 7 memory types (Decision/Pattern/Preference/Style/Habit/Insight/Context)
✅ Self-hostable ($5/month vs $150+ for alternatives)

vs. Native AI Memory

✅ Persistent across sessions (not just context window)
✅ Cross-platform (same memory in Claude, Cursor, Code)
✅ Structured relationships (not just RAG)
✅ Infinite scale (no context window limits)

Real-World Results

Code Review That Knows Your Standards

Before AutoMem:
"Consider adding error handling here."

After AutoMem:
"Missing your standard try/except pattern. Based on your PR#127
review comments, you always wrap database calls with specific
logging for timeouts. Apply the same pattern here?"

Decisions With Context

Before AutoMem:
"Both approaches have tradeoffs..."

After AutoMem:
"You chose PostgreSQL over MongoDB for similar use case in Q1 2024.
Your decision memo cited team expertise and operational simplicity.
Same factors apply here - go with Postgres."

Documentation

MCP Client & Integrations (this repo)

📦 Installation Guide - MCP client setup for all platforms
🌐 Remote MCP via SSE - Connect ChatGPT, Claude Web/Mobile, ElevenLabs
🎯 Cursor Setup - IDE integration with rules
🤖 Claude Code Hooks - Automated capture setup
💻 Warp Terminal Setup - Terminal integration
🚀 OpenAI Codex Setup - Codex CLI/IDE/Cloud integration
📖 MCP Tools Reference - All memory operations

AutoMem Service (separate repo)

🏗️ AutoMem Service - Backend repository
🚀 Service Installation - Local, Railway, Docker deployment
⚙️ API Documentation - REST API reference

The Science Behind AutoMem

The AutoMem service implements cutting-edge 2025 research:

HippoRAG 2 (OSU, June 2025): Graph-vector approach achieves 7% better associative memory
A-MEM (July 2025): Dynamic memory organization with Zettelkasten principles
MELODI (DeepMind, 2025): 8x memory compression without quality loss
ReadAgent (DeepMind, 2024): 20x context extension through gist memories

This MCP package provides the bridge between your AI and that research-validated memory system.

Community & Support

📦 NPM Package - This MCP client
🔬 AutoMem Service - Backend repo with deployment guides
🐛 GitHub Issues - Bug reports and feature requests
🐦 @verygoodplugins - Updates and announcements

Quick Links

MCP Client Setup

Installation Guide - MCP client setup for all platforms
Cursor Integration - IDE rules and configuration
Claude Code Hooks - Automated memory capture
Warp Terminal - Terminal integration
OpenAI Codex - Codex integration
Changelog - Release history

AutoMem Service

Service Repository - Backend source code
Service Installation - Local, Railway, Docker deployment

Contributing

We welcome contributions! Please:

Fork the repository
Create a feature branch
Make your changes with tests
Submit a pull request

License

MIT - Because great memory should be free.

Ready to give your AI perfect memory?

npx @verygoodplugins/mcp-automem setup

Built with obsession. Validated by neuroscience. Powered by graph theory. Works with every MCP-enabled AI.

Designed by Jack Arturo at Very Good Plugins 🧡

Transform your AI from a tool into a teammate. Start now.

Name		Name	Last commit message	Last commit date
Latest commit History 28 Commits
dist		dist
screenshots		screenshots
src		src
templates		templates
.gitattributes		.gitattributes
.gitignore		.gitignore
CHANGELOG.md		CHANGELOG.md
CLAUDE.md		CLAUDE.md
INSTALLATION.md		INSTALLATION.md
LICENSE		LICENSE
README.md		README.md
env.example		env.example
files.zip		files.zip
mcp-automem.code-workspace		mcp-automem.code-workspace
package-lock.json		package-lock.json
package.json		package.json
tsconfig.json		tsconfig.json

License

verygoodplugins/mcp-automem

Folders and files

Latest commit

History

Repository files navigation

AutoMem MCP: Give Your AI Perfect Memory 🧠

The Problem We Solve

What You Get

🧠 Persistent Memory Across Sessions

🏆 Graph-Vector Architecture

🚀 Works Everywhere You Code

See It In Action

Claude Desktop with Custom Instructions

Cursor IDE with Memory Rules

Claude Code with Session Memory

OpenAI Codex with Memory Rules

Warp Terminal with Memory Rules

Your AI Learns Your Code Style

Decisions That Feel Like Yours

Quick Start

1. Set Up AutoMem Service

2. Install MCP Client

3. Platform-Specific Setup

New: Remote MCP over SSE

SSE Platforms in Action

What Happens Next

Architecture

Features

Core Memory Operations

Platform Integrations

Cursor IDE

Claude Code

Claude Desktop

Warp Terminal

Why AutoMem MCP?

vs. Building Your Own

vs. Other Memory Solutions

vs. Native AI Memory

Real-World Results

Code Review That Knows Your Standards

Decisions With Context

Documentation

MCP Client & Integrations (this repo)

AutoMem Service (separate repo)

The Science Behind AutoMem

Community & Support

Quick Links

MCP Client Setup

AutoMem Service

Contributing

License

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