Agentic AI

Agentuity CLI Made Simple: Deploy AI Agents Without Infrastructure

Learn how to use the Agentuity CLI to build and deploy AI agents without complex infrastructure. A beginner-friendly guide to faster AI development.

By Ananya Rajeev 10 min read
Agentuity CLI AI Agents

The Problem with Building AI Agents Today

Building and deploying AI agents doesn’t have to feel overwhelming. With the Agentuity CLI, developers can skip the headache of configuring cloud infrastructure and focus entirely on creating smarter agents. This beginner-friendly tool simplifies the entire process—from setup to deployment—making it possible to go from idea to production with just a few commands.

The path to production-ready AI agents are rarely a straight line. It can involve multiple manual steps, from setting up a project to configuring a deployment pipeline and monitoring performance. For a beginner eager to experiment with AI, this infrastructure hurdle can be a major roadblock. The complexity of managing these foundational components can distract from the core mission: creating intelligent, autonomous agents.

The Agentuity CLI as Your Command Center

The Agentuity platform was designed to solve this very problem. Its mission is to “rebuild the cloud for AI agents” by providing a fully agentic infrastructure and the necessary tools for creating agents that are fully operated by AI. Theagentuity cli is the primary tool for interacting with this new platform. It serves as a command center that abstracts away the underlying infrastructure complexity.

The agentuity cli is a core part of Agentuity’s comprehensive toolkit, which also includes a web interface and a pre-built agent library. This command-line tool provides a first-class developer experience designed for rapid iteration. It is the embodiment of the platform’s core philosophy: “Build agents, not infrastructure”. By simplifying complex operations into single commands, the CLI offers a direct and fast path to production. It handles many of the time-consuming tasks that are typically associated with cloud deployment, from network configuration to security, allowing developers to focus on the creative work of building their agents.

The Agentuity Advantage: Simplicity and Power

A Unified Platform for Any AI Agent

One of the most notable advantages of the agentuity cli is its universal compatibility. Unlike tools that lock a developer into a specific language or framework, Agentuity is designed to be flexible. The platform supports a variety of tech stacks, including Python, Node.js, and Bun. A developer can use their preferred programming language to build their agent’s logic.

This flexibility extends to popular AI agent frameworks as well. Agentuity infrastructure enables seamless collaboration between agents built with different tools, such as LangChain and CrewAI. This means a developer is not required to learn a new framework to get started on the platform. The CLI itself acts as a universal control plane. Its core commands, such asagentuity dev and agentuity deploy, remain consistent regardless of whether the developer is using the Python or JavaScript SDK. This uniformity allows a developer to switch between languages and frameworks without learning a new set of deployment tools, creating a more cohesive and productive workflow.

A “Single Command” Path to Production

The primary promise of the agentuity cli is its ability to get an agent from a local development environment to a live, production-ready state with a single command.1 For a beginner, this is a significant benefit. In traditional development, the deployment phase is often the most complex and error-prone part of the process, involving multiple steps, configuration files, and service dependencies.

The agentuity deploy command automates this entire process. It handles bundling the agent and deploying it to the cloud without the need to manually configure infrastructure components like IAM, security groups, or load balancers. The simplicity of this command fundamentally changes the developer experience. It abstracts away a major part of the AI agent development lifecycle, making the process faster and more accessible for new users.

Your First Project: A Step-by-Step Guide

The agentuity cli provides a clear and intuitive path for a beginner to get a project up and running. The entire workflow can be summarized in a few simple commands.

CommandPurposeExample
`curl…sh`Installs the agentuity cli
agentuity loginAuthenticates your account with the cloud platformagentuity login
agentuity newCreates a new project from a templateagentuity new
agentuity devRuns your agent project locally for testing and debuggingagentuity dev
agentuity deployDeploys your agent to the cloudagentuity deploy

Step 1: Installing the Agentuity CLI

The first step is to install the command-line tool. Agentuity provides a simple installation script for Mac, Linux, and Windows Subsystem for Linux (WSL). A developer can run a single curl command to get the CLI on their system.

  • Mac and Linux: Open your terminal and run: curl -fsS https://agentuity.sh | sh
  • Mac (Alternative): If you prefer to use Homebrew, you can install the CLI with: brew install agentuity/tap/agentuity.
  • Windows: Native Windows installation is no longer supported. The official documentation recommends using Windows Subsystem for Linux (WSL) and running the installation script from there. This approach provides a consistent, Unix-like command-line environment for developers, which is a common strategy for modern cross-platform tools.

Step 2: Authentication and Project Creation

Once the CLI is installed, you can connect to the Agentuity Cloud. If you are a new user, you can create an account directly from the terminal with agentuity auth signup. If you already have an account, you can log in with agentuity login. This command will open a browser window to complete the authentication process.

After authenticating, you can create your first project. The agentuity new or agentuity create [name] command creates a new project using a pre-configured template. This step is a critical part of the simplified workflow. Instead of manually cloning a repository, installing dependencies, and configuring a project structure, the CLI handles all of these tasks in a single action. This is the reason a beginner can go from zero to a working project in minutes.

Step 3: Developing and Testing Locally with agentuity dev

With your project created, the next step is to run it locally. The agentuity dev command starts a development server on your machine.

The dev command is more than just a local server; it creates a bridge between your local development environment and the Agentuity Console.1 This feature, known as “DevMode,” connects your local agent to the web interface for real-time debugging and visualization. This provides a unique hybrid development experience where you can work on your local machine while using the platform’s advanced observability tools to test and debug your multi-agent system.1

Step 4: Deploying Your Agent to the Cloud

Once you are satisfied with your agent’s performance in local development, you can deploy it to the Agentuity Cloud. The agentuity deploy command handles the entire process.

The command takes your project, bundles it, and deploys it, making it accessible via the Agentuity platform. The platform’s native infrastructure handles the complexities of deployment, so you can skip manual configuration steps. This single command abstracts away what is traditionally the most complex and time-consuming part of the AI agent development lifecycle, allowing you to focus on the agent’s logic.

Beyond the Basics: Advanced Commands and Features

Once a user is comfortable with the core workflow, the agentuity cli provides a comprehensive set of commands for more advanced use cases.

CommandPurposeExample
agentuity envManages project-specific environment variables and secretsagentuity env set KEY=VALUE --secret
agentuity upgradeUpgrades the CLI to the latest versionagentuity upgrade
agentuity versionDisplays the current CLI versionagentuity version check
agentuity projectManages projects (list, delete)agentuity project delete [name]
agentuity agentManages individual agents within a project (create, list, delete, test)agentuity agent test --agent-id <id>

Managing Your Project and Environment

The CLI provides tools for granular project management, including commands to list all projects on your account (agentuity project list) and delete them when they are no longer needed (agentuity project delete).

It also offers robust environment management. The agentuity env set command allows a developer to configure environment variables for third-party integrations, such as social media platform APIs. A key security feature is the ability to set sensitive information as asecret using the --secret flag. This indicates the CLI is designed not just for simple projects but also for production-level use.

Keeping Your CLI Up-to-Date

A hallmark of a well-maintained tool is a simple update process. The agentuity cli includes a built-in upgrade command to ensure you are always using the latest version. You can also use

agentuity version to check your current version and agentuity version check to see if a newer version is available. The existence of these commands signals that the CLI is a living, evolving product with ongoing development and support.

A Look at Agent-Specific Commands

For more complex applications, the agentuity cli provides a specific set of commands for managing individual agents within a project. These commands, which include

agentuity agent create, agentuity agent list, and agentuity agent test, allow for more granular control. This shows a clear hierarchy of control, from project-level commands down to the individual agent, which is essential for managing sophisticated multi-agent systems.

The Broader Agentuity Ecosystem

The agentuity cli is a powerful tool, but it is not an isolated one. It works in concert with the broader Agentuity ecosystem to provide a seamless development experience.

Seamless Integration Beyond the CLI

While the CLI handles the management and deployment of agents, the SDKs are where a developer writes the agent’s core logic. Agentuity provides comprehensive SDKs for Python and JavaScript, which contain a set of tools for creating intelligent, event-driven agents. For example, a developer can define an agent’s behavior using the Python SDK and then use theagentuity deploy command to get it live. The CLI is not a replacement for coding; it is a productivity enhancer that bridges the gap between the developer’s local code and the live, cloud-based application. The CLI serves as the control panel, while the SDKs provide the building blocks for the agent’s intelligence.

Building Collaborative Multi-Agent Systems

The agentuity cli also serves as the gateway to a more advanced style of AI agent development: collaborative multi-agent systems. The platform’s architecture allows for the orchestration of multiple interconnected agents that can communicate with each other. A feature calledhandoff enables seamless communication between agents, even if they are built with different frameworks. This allows developers to design and orchestrate complex workflows where specialized agents handle different parts of a task, such as a “Copywriter Agent” creating content and a “Scheduler Agent” handling its distribution.

Furthermore, the platform’s intelligent routing system allows agents to connect to various input and output channels. This includes chat, webhooks, email, SMS, and popular services like Discord and Telegram. This capability means theagentuity cli is not just for deploying a single, isolated agent; it is for orchestrating entire systems that can respond to events and interact with the world through multiple channels.

Conclusion: Ready to Build

The agentuity cli is a significant tool in the world of AI agent development. It removes the traditional complexity of cloud infrastructure, empowering developers to focus on the creative work of building intelligent agents.

By providing a unified, single-command workflow, the CLI simplifies the entire development lifecycle, from project creation to live deployment. It is designed to work with your preferred programming language and framework, giving you the flexibility to build with your own stack. The tool’s focus on a first-class developer experience, coupled with the Agentuity platform’s ability to handle multi-agent collaboration and varied communication channels, makes it a powerful choice for both beginners and experienced developers. The core philosophy is clear: focus on your agent’s logic, and let Agentuity handle the deployment. This approach is poised to make AI agent development more accessible and efficient than ever before.

Agentuity CLI AI Agents
Agentuity CLI AI Agents

🔗 Further Reading & Resources

📚 Internal Links (Ossels AI Blog)

🌍 External Links (Authoritative Resources)

Ananya Rajeev

Ananya Rajeev is a Kerala-born data scientist and AI enthusiast who simplifies generative and agentic AI for curious minds. B.Tech grad, code lover, and storyteller at heart.