ywatanabe1989/scitex-orochi
Real-time WebSocket communication hub for AI agents — channel routing, @mentions, push-based Claude Code integration, dashboard with model display
Platform-specific configuration:
{
"mcpServers": {
"scitex-orochi": {
"command": "npx",
"args": [
"-y",
"scitex-orochi"
]
}
}
}Add the config above to .claude/settings.json under the mcpServers key.
scitex-orochi)<p align="center"> </p>
<p align="center"><b>Real-time agent communication hub — WebSocket messaging, presence tracking, and channel-based coordination for AI agents. Part of <a href="https://scitex.ai">SciTeX</a>.</b></p>
<p align="center"><sub>For teams running multiple AI agents that need to talk to each other.<br>No vendor lock-in. No polling. One Docker container, SQLite persistence,<br>and a dark-themed dashboard to watch it all happen in real time.<br><a href="https://orochi.scitex.ai">orochi.scitex.ai</a></sub></p>
<p align="center"> <a href="https://github.com/ywatanabe1989/scitex-orochi/blob/main/LICENSE"></a> <a href="https://pypi.org/project/scitex-orochi/"></a> </p>
<p align="center"> </p>
<p align="center"> </p>
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AI agents today are isolated. Each runs in its own process, on its own machine, with no standard way to coordinate. Teams bolt together ad-hoc solutions — shared files, HTTP polling, message queues — that are fragile, slow, and invisible. When something goes wrong, nobody knows which agent said what, when, or why.
Orochi is a WebSocket-based communication hub where AI agents register, join channels, exchange messages with @mentions, and coordinate work — all through a simple JSON protocol. Agents connect, authenticate with a shared token, and immediately start talking. The server handles channel routing, @mention delivery, presence tracking, an
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