AgentStack provides a command-line interface (CLI) for rapidly scaffolding and developing AI agent projects. It aims to simplify the initial setup and boilerplate code generation, allowing developers to focus on agent logic rather than framework configuration. The tool supports multiple popular agent frameworks and LLM providers, abstracting away complex dependencies.

How It Works

AgentStack acts as a project generator and utility suite, abstracting underlying agent frameworks (like CrewAI, LangGraph) and LLM providers (via LiteLLM). It generates a standardized project structure, handles dependency management, and provides CLI commands for generating agent components and adding tools. This approach offers a curated, opinionated starting point, reducing the initial configuration burden and promoting a cohesive development experience across different underlying technologies.

Quick Start & Requirements

• Install via curl --proto '=https' --tlsv1.2 -LsSf https://install.agentstack.sh | sh or uv pip install agentstack.
• Requires Python 3.10+.
• Create a project with agentstack init <project_name>.
• Run with agentstack run.
• Official Quickstart Guide: https://docs.agentstack.sh/ (Note: Link provided in README is a general docs link, not specific to quickstart)
• Video Tutorial: https://www.youtube.com/watch?v=4_f47h7_07A

Highlighted Details

• Supports multiple LLM providers via LiteLLM and agent frameworks like CrewAI, LangGraph, OpenAI Swarms, and LlamaStack.
• Features a large repository of framework-agnostic tools, easily added via agentstack tools add.
• Includes AgentOps observability baked in by default.
• CLI commands for generating agents, tasks, and adding tools streamline development.

Maintenance & Community

• Active development by "AgentOps-AI".
• Community support via Discord: https://discord.gg/Qh8f27fG
• Contribution guidelines are available.

Licensing & Compatibility

• Licensed under the MIT License.
• Permissive license suitable for commercial use and integration into closed-source projects.

Limitations & Caveats

The project is relatively new, with production deployment features noted as "coming soon." While it supports various frameworks, developers still need to understand the underlying agent development concepts.