Self-Hosted AI Agent Memory Platforms

Containerized, always-on AI agents with persistent memory. No cloud dependency. Your data stays on your infrastructure. Memoh, LocalAGI, and agent-memory compared.

Privacy-First Containerized No Cloud MIT License

The Case for Self-Hosted AI Agent Memory

Cloud AI agents send your conversations to third-party servers. For personal assistants, that's acceptable. For enterprise teams handling sensitive data, it's a compliance nightmare. Self-hosted AI agent platforms solve this:

Data never leaves your infrastructure — no cloud dependency
GDPR Article 28 compliance — no third-party data processor agreements needed
Full control — audit every interaction, every memory access
Cost predictable — fixed infrastructure cost vs per-call cloud fees
Works offline — no internet required after setup

"Hybrid split: Cloud inference for frontier model capability, local-first memory and indexing for privacy." — Memoh on GitHub

Self-Hosted AI Agent Platforms Compared

Memoh

Always-on containerized AI agents. Multi-platform (Discord, Telegram, Feishu, WeChat, etc). Local-first memory. MIT.

LocalAGI

Drop-in OpenAI API replacement. Self-hostable on CPU/GPU. Maximum privacy. AGPL.

agent-memory

MCP v3.2 server with AES-256 + TTL. Works with any MCP agent. MIT license.

Platforms Full Comparison

Feature	Memoh	LocalAGI	agent-memory
★ agent-memory	MCP server	MCP server	MCP v3.2
Encryption	—	—	AES-256
TTL	—	—	Yes
Containerized	Docker	Docker	—
Always-On	Yes	Yes	—
Multi-Platform	10+ channels	—	Any MCP agent
Privacy	Local-first	Maximum	Zero cloud
License	MIT	AGPL	MIT

Memoh — GitHub (4 weeks ago)

"Self hosted, always-on AI agent platform run in containers. Create multiple bots with long memory, and connect them to Telegram, Discord, Feishu (Lark), Matrix, etc. Like OpenClaw." — memohai/Memoh on GitHub

One-command install:

curl -fsSL https://memoh.sh | sudo sh
# Visit http://localhost:8082 after startup
# Default login: admin / admin123

Features:

Containerized — each bot in its own isolated container
Hybrid privacy — cloud inference + local memory
Multi-bot and multi-user — private and group chats
MCP tools support
Web UI for configuration — no coding required

LocalAGI — GitHub (Feb 28, 2026)

"A powerful, self-hostable AI Agent platform designed for maximum privacy and flexibility. A complete drop-in replacement for OpenAI's Responses APIs with advanced agentic capabilities." — mudler/LocalAGI on GitHub

Add MCP Memory to Any Self-Hosted Agent

agent-memory works with any MCP-compatible agent, including self-hosted ones:

# Connect agent-memory to Memoh, LocalAGI, or any MCP agent
pip install agent-memory

python -m agent_memory.mcp_server \\
  --storage json \\
  --path ./memory.json \\
  --host 0.0.0.0

# Your agent now has:
# - AES-256 encrypted persistent memory
# - TTL auto-expiration
# - Semantic search
# - MCP v3.2 native

agent-memory on GitHub Memoh on GitHub