Opencode Systems

Free

Opencode Systems is an open-source coding agent for Workflow Automation. You run it yourself, so your code stays local.

It sits between you and an AI model you already pay for. You type what you want. It writes and runs code for you.

It is new enough that some parts still feel rough. Early users trade polish for control over their data.

Open it if you want a self-hosted AI coding assistant that keeps your code private. Skip it if you want something polished that just works out of the box.

It fits a narrow set of people who want control more than convenience.

• Developers prioritizing code privacy: Your code never leaves your machine. You do not trust cloud tools with your source.
• Users wanting self-hosted AI coding tools: You run the tool yourself. You own the stack and the risk.
• Developers comfortable managing their own AI API keys: You bring your own OpenAI, Anthropic, or xAI keys. You pay your own way.
• Users who prefer open-source tools with modifiable code: You can change how it works. You inspect what runs on your machine.
• Those needing flexible deployment across terminal, desktop, or IDE: You pick how you work: command line, app window, or inside your editor.
• Users who prefer browser-based interfaces over terminal: You run a local web server and point your browser at it.
• Developers needing network-accessible local AI coding environment: You bind to 0.0.0.0 and reach it from another device on your LAN.
• Teams wanting to share sessions across multiple devices on LAN: You use mDNS discovery so teammates find it at opencode.local.
• Users who value safety boundaries when exploring codebases: You switch to a read-only "plan" agent so you do not break things by accident.
• Early adopters comfortable with beta software: You expect rough edges. You report bugs instead of waiting for polish.

These are the parts you notice after a few sessions.

• The dual-agent safety model: You press Tab to switch between "build" and "plan." Plan asks before it runs commands. You explore without fear.
• Flexible interfaces: You start in terminal, move to browser, or add an IDE extension. You do not pick one way to work.
• Network sharing built in: You bind to a custom port, open to your LAN, and let teammates connect. No extra tunnel needed.
• Open source under MIT: You read the code, fork it, or patch it. You are not stuck with what the vendor ships.
• Bring your own model: You plug in the AI provider you already use. You are not locked into one company's model.

You have a few paths in, but the web route is the smoothest start.

1. Run the install script to drop binaries into ~/.opencode/bin.
2. Start the web server with the CLI command.
3. Point your browser to the local address it prints.
4. Add your AI provider key in settings.
5. Describe what you want built and let the agent work.

Skip it when you need polish, or when self-hosted means more work than you want.

• Sparse documentation: You hunt for answers. The README is thin and the full docs live elsewhere.
• Setup varies by machine: You might fight with dependencies. Some environments need extra fiddling.
• Desktop app is beta: You risk crashes. The project warns you to remove old versions before updating.
• Unclear edge from paid tools: You wonder why you did not just use Cursor or Windsurf. The difference is control, not features.
• Hidden costs: The tool is free, but you pay for AI calls. You track your own spending.