Brightsy CLI

The Brightsy Command Line Interface (CLI) provides a powerful way to interact with Brightsy AI directly from your terminal, enabling streamlined workflows and integration options.

Installation

Install the Brightsy CLI globally using npm:

npm install -g brightsy-cli

Or run it directly with npx:

npx brightsy-cli

Configuration

Before using the CLI, you need to set up your API key and agent ID:

brightsy configure <agent_id> <api_key>

Additional Configuration Options

• View current configuration

  brightsy configure --view
  

• Reset configuration

  brightsy configure --reset
  

Chat Functionality

The CLI allows you to have conversations with your Brightsy AI agent directly from the terminal.

Starting or Continuing a Chat

To start a new chat or continue the active chat:

brightsy "Your message here"

Chat Management

• Continue a specific chat

  brightsy chat "Your message here" --chat-id <chat-id>
  

  Note: The --chat-id parameter is optional. If omitted, the command will use the active chat.

• End the current chat session

  brightsy chat --end
  

• List recent chats

  brightsy chat --list
  

MCP Integration

The Brightsy CLI includes Model Context Protocol (MCP) server functionality, allowing you to integrate Brightsy AI with compatible applications like Cursor and Claude Desktop.

Running the MCP Server

Start the MCP server directly:

brightsy mcp

For detailed information on MCP integration, see the MCP documentation.

Use Cases

Development Workflows

• Quick Information Retrieval: Get answers without leaving your terminal
• Code Generation: Generate code snippets directly in your workflow
• Project Management: Track tasks and issues through conversations

Automation

• CI/CD Integration: Include Brightsy AI in your automated workflows
• Scheduled Tasks: Set up cron jobs that interact with Brightsy AI
• Batch Processing: Process multiple requests through scripts

System Integration

• Custom Tooling: Build your own tools on top of the Brightsy CLI
• Environment Monitoring: Use in conjunction with system monitoring tools
• Data Processing Pipelines: Incorporate AI analysis in your data workflows

Best Practices

• Environment Variables: Consider storing your API key and agent ID as environment variables
• History Management: Regularly clean up your chat history for better performance
• Scripting: Use the CLI in bash/shell scripts for more complex workflows
• Context Management: Keep related conversations in the same chat for better context awareness

Troubleshooting

• Authentication Issues: Verify your API key and agent ID
• Connection Problems: Check your internet connection and firewall settings
• Version Conflicts: Ensure you're using the latest version of the CLI

For more detailed information, refer to the GitHub repository documentation.