# AgentStack: The Fastest Way to Build Robust AI Agents This repository profile is provided by osrepos.com, an open source repository discovery platform. Source: osrepos.com Repository profile: https://osrepos.com/repo/agentops-ai-agentstack Generated for open source discovery and AI-assisted research. AgentStack is a powerful command-line tool designed to simplify the development of AI agents. It provides a scaffold for agent projects, offering CLI utilities for code generation and managing various LLMs, frameworks, and tools. This project aims to make building robust AI agents accessible and efficient for developers. GitHub: https://github.com/AgentOps-AI/AgentStack OSRepos URL: https://osrepos.com/repo/agentops-ai-agentstack ## Summary AgentStack is a powerful command-line tool designed to simplify the development of AI agents. It provides a scaffold for agent projects, offering CLI utilities for code generation and managing various LLMs, frameworks, and tools. This project aims to make building robust AI agents accessible and efficient for developers. ## Topics - Python - AI - Agents - Development Tools - CLI - Frameworks - Open Source - Machine Learning ## Repository Information Last analyzed by OSRepos: Mon Apr 27 2026 16:43:37 GMT+0100 (Western European Summer Time) Detail views: 3 GitHub clicks: 2 ## Safety Notice OSRepos shares public repositories for knowledge and discovery only. Review source code, dependencies, licenses, and security implications before running or installing anything. ## Content ## Introduction AgentStack is a powerful command-line interface (CLI) tool designed to streamline the development of robust AI agents. It provides a comprehensive scaffold for your agent projects, simplifying the initial setup and offering numerous CLI utilities for efficient code generation throughout the development process. Built with Python, AgentStack supports a wide array of LLMs and popular agent frameworks like CrewAI, LangGraph, OpenAI Swarms, and LlamaStack, ensuring a flexible and curated development experience. It also integrates observability with AgentOps by default and maintains a large repository of framework-agnostic tools. ## Installation Getting started with AgentStack is straightforward. You will need Python 3.10+ installed on your system. To install AgentStack, you can use the `curl` command: sh curl --proto '=https' --tlsv1.2 -LsSf https://install.agentstack.sh | sh Alternatively, you can install it using `uv pip`: sh uv pip install agentstack For more detailed installation methods, refer to the [official documentation](https://docs.agentstack.sh/installation "AgentStack Installation Guide" target="_blank"). ## Examples AgentStack simplifies the creation and management of your AI agent projects. **Creating a New Agent Project:** To start a new project, run the `init` command: sh agentstack init This command creates a new directory with your project name, generates the initial structure, and installs dependencies. After initialization, navigate into your project folder and install its dependencies: sh cd uv pip install Then, you can run the default agent: sh agentstack run **Building Agent Functionality:** AgentStack provides commands to quickly generate agents and tasks: bash agentstack generate agent/task You can modify these by editing the `agents.yaml` and `tasks.yaml` configuration files in `src/config`. **Adding Tools:** AgentStack emphasizes easy access to a vast collection of framework-agnostic tools. You can add tools with a simple command: bash agentstack tools add For a complete list of available tools, visit the [AgentStack Tools documentation](https://docs.agentstack.sh/tools/core "AgentStack Core Tools" target="_blank"). **Templates:** Pre-built templates are also available to accelerate your project development. Explore them in the [templates documentation](https://docs.agentstack.sh/templates "AgentStack Templates" target="_blank"). ## Why Use AgentStack? AgentStack is built on several core philosophies that aim to enhance the AI agent development experience: * **Agents Should Be Easy:** It simplifies the "from scratch" process by providing a simple boilerplate, similar to `create-react-app`, offering a cohesive and curated experience on top of popular agent frameworks and LLM providers. * **No Configuration Required:** AgentStack handles reasonable default configurations for both development and production builds, allowing you to focus purely on writing code. * **No Lock-In:** While providing a quick start, AgentStack is designed to be fully customizable. You can modify your setup at any time, ensuring flexibility as your project evolves. * **Provider Agnosticism:** The tool is designed to be interoperable across different layers of your agent stack, supporting various frameworks and LLM providers without vendor lock-in. AgentStack is not a low-code solution, but rather a powerful head-start for developers looking to build complex AI agent projects efficiently. For a visual guide, check out the [video tutorial](https://www.loom.com/share/68d796b13cd94647bd1d7fae12b2358e?sid=7fdf595b-de84-4d51-9a81-ef1e9c8ac71c "AgentStack Video Tutorial" target="_blank") on building a web scrape agent. ## Links * [GitHub Repository](https://github.com/agentstack-ai/AgentStack "AgentStack GitHub Repository" target="_blank") * [Official Documentation](https://docs.agentstack.sh "AgentStack Official Documentation" target="_blank") * [Discord Community](https://discord.gg/JdWkh9tgTQ "AgentStack Discord Community" target="_blank") * [Video Tutorial](https://www.loom.com/share/68d796b13cd94647bd1d7fae12b2358e?sid=7fdf595b-de84-4d51-9a81-ef1e9c8ac71c "AgentStack Video Tutorial" target="_blank") * [AgentStack Tools](https://docs.agentstack.sh/tools/core "AgentStack Core Tools" target="_blank") * [AgentStack Templates](https://docs.agentstack.sh/templates "AgentStack Templates" target="_blank")