How to deploy an autonomous coding agent that reads code, runs commands, and collaborates in your IDE and terminal
Imagine a coding partner that grasps project structure, modifies multiple files simultaneously, executes terminal commands, and collaborates with other agents when needed. Cline is an open-source coding agent that performs these tasks, available as an editor extension for VS Code or JetBrains, a terminal CLI, a desktop app, and an SDK. This allows developers to manage the entire process from code writing and debugging to deployment as a single workflow.
Understanding and modifying the entire project
Cline reads the project's file structure, understands relationships between files, and performs coordinated changes across multiple files. It detects linter or compiler errors in real-time during work, fixing issues like missing imports or type mismatches before the user sees them. In VS Code and JetBrains, all edits are displayed as diffs, allowing for review, modification, and reversal, while checkpoints make it easy to undo the agent's work. In the terminal, it directly executes commands such as installing packages, running build scripts, executing tests, or proceeding with deployments. Even for long-running processes like development servers, it continues operating in the background, immediately reacting to compile errors, test failures, or server crashes whenever new output appears.
Separating planning and execution with rule application
Cline allows switching between Plan mode and Act mode. In Plan mode, it explores the codebase, asks additional questions, and formulates a strategy, while Act mode executes that plan. File edits and terminal commands require user approval by default, but enabling auto-approval mode allows for autonomous execution. You can define project-specific rules such as coding standards, architecture rules, deployment procedures, and testing requirements in the .clinerules file, which the CLI, VS Code extension, and JetBrains plugin recognize automatically. Additionally, you can use skills to configure the model to load specific rules when needed.
Connecting various models and external systems
Cline is not dependent on a specific AI provider and can use various models including Anthropic, OpenAI, Google, OpenRouter, AWS Bedrock, Azure, GCP Vertex, Cerebras, Groq, Ollama, and LM Studio. You can extend functionality through plugins or MCP servers, and use the SDK to register tools or add lifecycle hooks to implement logging, auditing, policy enforcement, and domain-specific features. You can use servers created by the community or ask Cline to create custom tools on the fly.
Multi-agent teams and scheduled automation
You can configure multi-agent teams where multiple agents collaborate on complex tasks. A coordinator agent divides tasks into subtasks, and each specialized agent performs them with its own tools and context. Team state is maintained across sessions, allowing work to resume from where it was interrupted. You can also set cron schedules to run agents periodically. This enables automatic generation of daily PR summaries, weekly dependency checks, and codebase health reports, with schedules persisting after restarts and running independently of terminal sessions. You can also connect to messaging platforms like Slack, Telegram, Discord, Google Chat, WhatsApp, and Linear to converse with the agent via chat.
Pre-use considerations
Cline is released under the Apache 2.0 license and is written in TypeScript. It is provided in various forms including a VS Code extension, JetBrains plugin, CLI, desktop app, and SDK, although the JetBrains plugin is not currently open-sourced. The CLI is installed with npm i -g cline, and the SDK with npm install @cline/sdk. The desktop app is provided as a native app for macOS and Windows, composed of a Tauri shell, Bun sidecar, and Next.js UI. To integrate into CI/CD pipelines, you can use headless mode to pipe input, receive JSON output, and chain commands. Users must select an AI model suitable for their workflow, define project rules in .clinerules, and extend functionality via MCP servers or plugins if necessary. When using autonomous mode, it is important to clearly set approval procedures for changes.
