OpenCode: A Terminal-First AI Coding Agent

Most AI coding tools today are IDE extensions or subscription-wrapped products that bundle the model cost into a monthly fee. OpenCode takes a different approach: it’s an open-source coding agent that runs in your terminal, connects to the models and providers you already use, and gets out of the way.

This article explains what OpenCode is, how it fits into a modern development workflow, and what makes it worth considering as a CLI coding assistant.

What “Terminal-First” Means in Practice

Terminal-first doesn’t mean terminal-only. OpenCode is available as a terminal-based TUI (Terminal User Interface), a desktop app, and an IDE extension. But the terminal is where it’s designed to feel most at home.

In practice, the terminal interface avoids typical desktop overhead, runs directly in your shell, and does not require a separate GUI to get started. You open your project directory, run opencode, and you’re in a full interactive coding session. The TUI is built for keyboard-driven workflows — sessions, model switching, file context, and commands are all accessible without leaving the keyboard.

For developers who already live in the terminal, this is a natural fit. For those who prefer a GUI, the desktop and IDE options are there.

Core Capabilities of the OpenCode AI Agent

OpenCode is more than a chat interface. The AI agent has access to a set of built-in tools it can invoke during a session:

• File operations: read, write, edit, and patch files directly
• Shell execution: run commands in your configured shell
• Search: grep file contents, glob patterns, list directories
• Code intelligence: navigate definitions, references, and symbols via LSP integration

This means you can ask OpenCode to add a feature, and it will read the relevant files, make the changes, and run a build check — without you manually copying code back and forth.

Plan Mode vs. Build Mode

One of the more practical features is the distinction between Plan and Build mode. In Plan mode, OpenCode drafts what it intends to do before touching any files. You review the plan, give feedback, and only then switch to Build mode to execute. This two-step approach reduces unwanted changes and gives you meaningful control over what the agent does.

Multi-Session Workflows

OpenCode persists sessions locally, so you can switch between conversations and pick up where you left off. You can switch between sessions, share a session link with a teammate via /share, and pick up where you left off. Shared sessions are opt-in — nothing is shared by default.

Flexible Model and Provider Support

OpenCode connects to a wide range of AI providers: Anthropic, OpenAI, Google Gemini, AWS Bedrock, Groq, Azure OpenAI, OpenRouter, and others. It also supports self-hosted models via a local endpoint, as well as GitHub Copilot if you already have that set up.

You configure providers through environment variables or a local .opencode.json file. API keys stay on your machine. The model you use for heavy reasoning tasks can differ from the one you use for routine cleanup, and you can switch models on the fly without restarting.

This flexibility is one of the clearest differences between OpenCode and subscription-based AI developer tools: you pay for what you use, with the providers you choose.

Extensibility: LSP, MCP, and Custom Commands

OpenCode integrates with the Language Server Protocol to give the agent access to real diagnostics from your language toolchain. Configure gopls, typescript-language-server, or any LSP-compatible server, and the agent can check for errors and suggest fixes grounded in actual compiler output.

For broader extensibility, OpenCode supports the Model Context Protocol (MCP), a standard for connecting AI agents to external tools and services. MCP servers can be added to your config, and their tools become available to the agent automatically.

Custom commands let you define reusable prompts as Markdown files — stored per-user or per-project — with named argument placeholders. A command like project:prime-context can run git ls-files, read your README, and set up the agent’s context in one step.

Where OpenCode Fits

The landscape of AI developer tools splits roughly into two categories: IDE-integrated assistants that work alongside your editor, and CLI agents that operate more autonomously on your codebase. OpenCode sits firmly in the second category, with the added flexibility of GUI options when you need them.

Conclusion

OpenCode offers a pragmatic alternative to subscription-locked AI coding assistants. By running in the terminal, supporting bring-your-own-provider configurations, and exposing extensibility through LSP, MCP, and custom commands, it gives developers direct control over how and where AI fits into their workflow. If you work across multiple projects, prefer configuring your own toolchain, or want an open-source coding agent you can inspect and extend, OpenCode is worth a close look. Start at opencode.ai and run /init in your first project to see how it reads your codebase before writing a single line.

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