Main
Treat it like “Git for AI content”: version conversation outputs, attribute changes, and keep an audit trail for teams.
Use the MCP hub to standardize server onboarding: one place to discover, configure, and namespace tools.
Start self-hosted with Docker Compose, then decide if you need external vector infra—the README also highlights embedded options.
For security, keep tokens/API keys in env vars and rotate them just like any internal platform credential.
README (excerpt)
plugged.in 🔌

Turn your AI conversations into permanent organizational memory
🚀 Get Started • 📚 Documentation • 🌟 Features • 💬 Community
🧩 Now Multi‑Arch Ready!
Plugged.in Docker images support both amd64 and arm64 architectures via a unified manifest.
🧠 v3.0.0 — Embedded RAG Vector Engine:
RAG now runs fully in-process using zvec (RocksDB + HNSW). No external services needed — document processing, chunking, and semantic search are all built-in.
🎯 The Problem We Solve
Every day, you have brilliant conversations with AI - strategy sessions with GPT-4, code reviews with Claude, analysis with Gemini. But when you close that chat window, all that knowledge vanishes. This is the "AI knowledge evaporation" problem.
💡 The Solution
plugged.in is the world's first AI Content Management System (AI-CMS) - a platform that transforms ephemeral AI interactions into persistent, versioned, and searchable organizational knowledge.
Think of it as "Git for AI-generated content" meets "WordPress for AI interactions".
✨ What Makes plugged.in Special
🧠 AI Memory That Persists
Your AI conversations become permanent assets. Every document is versioned, attributed, and searchable.
🤝 Multi-Model Collaboration
Claude writes v1, GPT-4 adds technical specs in v2, Gemini refines in v3 - all tracked and attributed.
🔌 Universal MCP Integration
Works with 1,500+ MCP servers. Connect any tool, any AI, any workflow - all through one interface.
Source-backed notes
- README provides a Docker Quick Start and opens the app at
http://localhost:12005. - README highlights a built-in MCP server hub and integration/discovery features.
- README includes platform stats and describes embedded vector/RAG options for self-hosting.
FAQ
- Do I need a separate vector DB?: Not always—README mentions embedded options; start simple and scale later.
- Is it only for MCP?: No—it's an AI knowledge platform, with MCP hub as one core module.
- What’s the fastest local path?: Use Docker Compose quick start and confirm you can log in and see the MCP hub UI.