
Open-source, self-hosted multi-agent orchestration with isolated containers, persistent workspaces, long-term memory, and zero telemetry.
Memoh is an open-source, self-hosted multi-agent platform and agent orchestrator. It is designed for running always-on agents in isolated containerized workspaces rather than simple chat sessions. According to the official site, Memoh provides container isolation, long-term memory, high concurrency, and zero telemetry. Search results for the official GitHub repository describe each agent as having its own computer-like environment with a desktop, filesystem, network access, and persistent workspace. It is useful for developers and teams building autonomous agent systems that need self-hosting, separation between agents, durable memory, and controlled infrastructure.
Product overview
Memoh is an open-source multi-agent hosting and orchestration platform, not one assistant. It gives each agent a workspace, browser or desktop, network, tools, memory, channels, schedules, plugins, and bot-scoped access controls on desktop or self-hosted servers.
Information as of August 18, 2026
Each bot can receive an isolated container with files, commands, network access, a browser, graphical desktop, MCP hosting, and long-term memory.[1]
Agents can communicate through web, email, Telegram, Discord, Lark, WeChat and other channels, and can run schedules, heartbeats, hooks, plugins, and skills.[1], [2]
Memoh separates channel-side chat permissions from workspace roles and supports more precise bot access rules when needed.[1]
Memoh's self-hosted software is free and published under AGPLv3. Operators supply their own infrastructure and model access; the managed SaaS is still described as coming soon, with no public price established.[1], [2]
Platforms: Desktop application, Web UI, CLI, Telegram, Discord, Lark, WeChat, Email[1], [2]
Access: Local desktop, Self-hosted Docker Compose server, Isolated container workspaces, Trusted local workspaces[1], [2]
87/100
Our subjective rating of how independently the product carries out its documented tasks, considering the human setup, input, approval and review it needs. This is not a measured success rate.
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