OpenCode

⚠️ Early Development Notice: This project is in early development and is not yet ready for production use. Features may change, break, or be incomplete. Use at your own risk.

A powerful terminal-based AI assistant for developers, providing intelligent coding assistance directly in your terminal.

Overview

OpenCode is a Go-based CLI application that brings AI assistance to your terminal. It provides a TUI (Terminal User Interface) for interacting with various AI models to help with coding tasks, debugging, and more.

Features

• Interactive TUI: Built with Bubble Tea for a smooth terminal experience
• Multiple AI Providers: Support for OpenAI, Anthropic Claude, Google Gemini, AWS Bedrock, and Groq
• Session Management: Save and manage multiple conversation sessions
• Tool Integration: AI can execute commands, search files, and modify code
• Vim-like Editor: Integrated editor with text input capabilities
• Persistent Storage: SQLite database for storing conversations and sessions
• LSP Integration: Language Server Protocol support for code intelligence
• File Change Tracking: Track and visualize file changes during sessions

Installation

# Coming soon
go install github.com/kujtimiihoxha/opencode@latest

Configuration

OpenCode looks for configuration in the following locations:

• $HOME/.opencode.json
• $XDG_CONFIG_HOME/opencode/.opencode.json
• ./.opencode.json (local directory)

Environment Variables

You can configure OpenCode using environment variables:

Configuration File Structure

{
  "data": {
    "directory": ".opencode"
  },
  "providers": {
    "openai": {
      "apiKey": "your-api-key",
      "disabled": false
    },
    "anthropic": {
      "apiKey": "your-api-key",
      "disabled": false
    }
  },
  "agents": {
    "coder": {
      "model": "claude-3.7-sonnet",
      "maxTokens": 5000
    },
    "task": {
      "model": "claude-3.7-sonnet",
      "maxTokens": 5000
    },
    "title": {
      "model": "claude-3.7-sonnet",
      "maxTokens": 80
    }
  },
  "mcpServers": {
    "example": {
      "type": "stdio",
      "command": "path/to/mcp-server",
      "env": [],
      "args": []
    }
  },
  "lsp": {
    "go": {
      "disabled": false,
      "command": "gopls"
    }
  },
  "debug": false,
  "debugLSP": false
}

Supported AI Models

OpenAI Models

Anthropic Models

Other Models

Usage

# Start OpenCode
opencode

# Start with debug logging
opencode -d

# Start with a specific working directory
opencode -c /path/to/project

Command-line Flags

Keyboard Shortcuts

Global Shortcuts

Chat Page Shortcuts

Editor Shortcuts

Logs Page Shortcuts

AI Assistant Tools

OpenCode's AI assistant has access to various tools to help with coding tasks:

File and Code Tools

Other Tools

Architecture

OpenCode is built with a modular architecture:

• cmd: Command-line interface using Cobra
• internal/app: Core application services
• internal/config: Configuration management
• internal/db: Database operations and migrations
• internal/llm: LLM providers and tools integration
• internal/tui: Terminal UI components and layouts
• internal/logging: Logging infrastructure
• internal/message: Message handling
• internal/session: Session management
• internal/lsp: Language Server Protocol integration

MCP (Model Context Protocol)

OpenCode implements the Model Context Protocol (MCP) to extend its capabilities through external tools. MCP provides a standardized way for the AI assistant to interact with external services and tools.

MCP Features

• External Tool Integration: Connect to external tools and services via a standardized protocol
• Tool Discovery: Automatically discover available tools from MCP servers
• Multiple Connection Types:
  • Stdio: Communicate with tools via standard input/output
  • SSE: Communicate with tools via Server-Sent Events
• Security: Permission system for controlling access to MCP tools

Configuring MCP Servers

MCP servers are defined in the configuration file under the mcpServers section:

{
  "mcpServers": {
    "example": {
      "type": "stdio",
      "command": "path/to/mcp-server",
      "env": [],
      "args": []
    },
    "web-example": {
      "type": "sse",
      "url": "https://example.com/mcp",
      "headers": {
        "Authorization": "Bearer token"
      }
    }
  }
}

MCP Tool Usage

Once configured, MCP tools are automatically available to the AI assistant alongside built-in tools. They follow the same permission model as other tools, requiring user approval before execution.

LSP (Language Server Protocol)

OpenCode integrates with Language Server Protocol to provide rich code intelligence features across multiple programming languages.

LSP Features

• Multi-language Support: Connect to language servers for different programming languages
• Code Intelligence: Get diagnostics, completions, and navigation assistance
• File Watching: Automatically notify language servers of file changes
• Diagnostics: Display errors, warnings, and hints in your code

Supported LSP Features

Configuring LSP

Language servers are configured in the configuration file under the lsp section:

{
  "lsp": {
    "go": {
      "disabled": false,
      "command": "gopls"
    },
    "typescript": {
      "disabled": false,
      "command": "typescript-language-server",
      "args": ["--stdio"]
    }
  }
}

LSP Integration with AI

The AI assistant can access LSP features through the diagnostics tool, allowing it to:

• Check for errors in your code
• Suggest fixes based on diagnostics
• Provide intelligent code assistance

Development

Prerequisites

• Go 1.23.5 or higher

Building from Source

# Clone the repository
git clone https://github.com/kujtimiihoxha/opencode.git
cd opencode

# Build the diff script first
go run cmd/diff/main.go

# Build
go build -o opencode

# Run
./opencode

Acknowledgments

OpenCode builds upon the work of several open source projects and developers:

• @isaacphi - LSP client implementation

License

OpenCode is licensed under the MIT License. See the LICENSE file for details.

Contributing

Contributions are welcome! Here's how you can contribute:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Please make sure to update tests as appropriate and follow the existing code style.