Mininglamp-OSS

Mininglamp-OSS / octo-server

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🐙 The Go backend powering OCTO — an open workplace built for humans × AI agents. REST & WebSocket APIs, Lobster (AI agent) orchestration, and WuKongIM real-time messaging control plane.

github.comMininglamp-OSS ai-agents apache2 chat collaboration digital-workplace
11
5
89% credibility
Found May 17, 2026 at 11 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Go
AI Summary

OCTO Server is the central brain of an open workplace platform. It lets organizations create AI assistants (called Lobsters) that can chat, collaborate in groups, manage threads and spaces, and work alongside human teammates. The backend connects web and mobile apps with real-time messaging, handles bot creation and authentication, and provides a complete collaboration toolkit. It's built to be self-hostable with automatic backups and runs under Apache 2.0 open source license.

How It Works

1
💬 You discover OCTO

You hear about a workplace platform where humans and AI agents work together seamlessly.

2
🤖 You create your AI assistant

You build a bot (called a Lobster) that can think and act on your behalf, handling conversations and tasks.

3
🔑 Your assistant connects to the chat

You give your bot a private password so it can log in, send messages, and respond to you in real-time.

4
👥 You chat and collaborate

Your bot joins group conversations and threads, helping coordinate work alongside your team.

5
You choose how to use it
🖥️
Use the app

Open the web or mobile app to chat with your AI-powered workspace.

⚙️
Manage everything

Use the admin console to control bots, users, and settings for your whole organization.

6
📦 Everything backs up automatically

Your workspace data is safely stored and backed up so nothing is ever lost.

🎉 Your workplace is ready

You have a powerful AI-augmented workspace where your digital assistant handles the thinking and doing, while you focus on judgment and taste.

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Star Growth

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AI-Generated Review

What is octo-server?

octo-server is a Go-powered backend that runs OCTO, an open workplace platform designed for human and AI agent collaboration. It exposes REST and WebSocket APIs that connect mobile apps, web clients, and admin consoles to a unified messaging and automation hub. The server handles user authentication, bot lifecycle management, and orchestrates AI agents called "Lobsters" that act as digital workmates. It drives real-time messaging through WuKongIM integration while managing its own business logic layer. The platform supports file uploads to multiple cloud storage providers, SMS/email verification, and scheduled backup jobs to Tencent COS.

Why is it gaining traction?

The AI agent orchestration built into the backend is the standout feature. Rather than treating bots as external integrations, octo-server treats them as first-class conversation participants with proper routing, session management, and tool execution. The multi-storage adapter support means teams can plug in their existing Aliyun OSS, MinIO, or Tencent COS setup without vendor lock-in. The entire ecosystem is open-source under Apache 2.0 with a Docker Compose setup for one-command deployment.

Who should use this?

Backend engineers evaluating self-hosted workplace chat platforms will find this most useful. Teams wanting to embed AI agents directly into messaging workflows should look here. Organizations already using WuKongIM can extend it with octo-server's REST layer and admin tooling. Small teams needing a complete communication backend without rolling their own from scratch could deploy the full stack. Teams wanting only the bot API for external integrations will find the bot_api module useful standalone.

Verdict

octo-server is a capable but immature project. The 11 stars and 0.8999% credibility score reflect an early-stage effort with limited community validation. The Go codebase shows thoughtful architecture with clean module boundaries, but test coverage varies significantly across modules. Documentation exists in both English and Chinese, though the Chinese-first approach suggests the primary audience is domestic. If you need a self-hosted workplace platform with built-in AI agent support, this delivers more out-of-the-box than rolling your own. For production use, wait for more community adoption or budget time to audit the codebase yourself.

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