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Kilo-Org_kilocode/packages/opencode/README.md
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# Kilo Code CLI
The AI coding agent built for the terminal. Generate code from natural language, automate tasks, and run terminal commands -- powered by 500+ AI models.
## Install
```bash
npm install -g @kilocode/cli
```
Or run directly with npx:
```bash
npx --package @kilocode/cli kilo
```
## Getting Started
Run `kilo` in any project directory to launch the interactive TUI:
```bash
kilo
```
Run a one-off task:
```bash
kilo run "add input validation to the signup form"
```
## Features
- **Code generation** -- describe what you want in natural language
- **Terminal commands** -- the agent can run shell commands on your behalf
- **500+ AI models** -- use models from OpenAI, Anthropic, Google, and more
- **MCP servers** -- extend agent capabilities with the Model Context Protocol
- **Multiple modes** -- Plan with Architect, code with Coder, debug with Debugger, or create your own
- **Sessions** -- resume previous conversations and export transcripts
- **API keys optional** -- bring your own keys or use Kilo credits
## Commands
| Command | Description |
| --------------------- | -------------------------- |
| `kilo` | Launch interactive TUI |
| `kilo run "<task>"` | Run a one-off task |
| `kilo auth` | Manage authentication |
| `kilo models` | List available models |
| `kilo mcp` | Manage MCP servers |
| `kilo session list` | List sessions |
| `kilo session delete` | Delete a session |
| `kilo export` | Export session transcripts |
Run `kilo --help` for the full list.
## Alternative Installation
### Homebrew (macOS/Linux)
```bash
brew install Kilo-Org/tap/kilo
```
### GitHub Releases
Download pre-built binaries from the [Releases page](https://github.com/Kilo-Org/kilocode/releases).
## Documentation
- [Docs](https://kilo.ai/docs)
- [Getting Started](https://kilo.ai/docs/getting-started)
## Links
- [GitHub](https://github.com/Kilo-Org/kilocode)
- [Discord](https://kilo.ai/discord)
- [VS Code Extension](https://kilo.ai/vscode-marketplace)
- [Website](https://kilo.ai)
## License
MIT