SwiftGate is an operating system for AI agents. Connect Claude Code, OpenCode, and other agents in one shared environment, alongside SwiftGate’s own agent harness. Give every agent shared knowledge, memory, peer communication, scheduled wakes, MCP integrations, and full action logs. Because agent traffic passes through SwiftGate, actions remain traceable. Use your API keys, connect local machines via the SwiftGate CLI, and manage agent teams from desktop, mobile, Apple Messages, or Telegram.
I started building SwiftGate because working with AI agents quickly became fragmented.
Claude Code, OpenCode, custom agents, MCP servers, different machines, different models, different memories — each could be useful on its own, but there was no shared layer where they could work together.
I wanted agents to become nodes in one system instead of isolated tools.
That led me to SwiftGate: a shared brain and runtime where agents can communicate, wake each other, access the same knowledge, use the same integrations, and leave a complete trace of what happened — regardless of where the agent itself came from.
I also wanted to keep the infrastructure open: bring your own API keys, connect your own machines, and increasingly run agents and models locally.
I’d love to hear what you would build with a setup like this, and what you think is still missing.