AI Agent Frameworks: Hands-On Comparison of AG2, Agno, AutoGen & More
This GitHub repository provides working Python code examples across multiple leading open-source AI agent frameworks—including AG2, Agno, and AutoGen—so developers can directly compare how each one handles agent creation, tool use, and multi-agent coordination. Instead of reading documentation alone, you can clone the repo and run side-by-side examples to find the right framework for your use case. It is actively maintained (last updated March 2026) and serves as a practical decision-making tool for teams evaluating AI agent infrastructure.
MISSION OBJECTIVES
- 01Clone the repository with `git clone https://github.com/martimfasantos/ai-agents-frameworks` and run the setup instructions to get at least one framework example executing locally within 20 minutes.
- 02Pick two frameworks from the included list (e.g., AG2 vs. Agno), run their equivalent example scripts side-by-side, and note differences in syntax verbosity, tool-calling approach, and output quality.
- 03Document your comparison in a one-page internal decision matrix covering ease of setup, multi-agent support, and LLM compatibility to share with your team before choosing a framework.
FIELD OPERATIONS
Automated Customer Support Triage Agent
Use this repo's examples as a foundation to build a multi-agent system where one agent classifies incoming support tickets by urgency, a second agent drafts responses, and a third escalates unresolved issues—comparing which framework (AG2, Agno, or AutoGen) delivers the cleanest handoff logic.
Competitive Intelligence Research Pipeline
Build a multi-agent workflow where one agent scrapes public competitor news, a second summarizes findings, and a third generates a structured weekly briefing—use the repo's framework examples to prototype in two different frameworks and benchmark speed and cost per run.
STRATEGIC APPLICATIONS
- →A software team evaluating AI agent infrastructure can use this repo to run real code in AG2, Agno, and AutoGen within a single afternoon, cutting weeks off their framework selection process before committing engineering resources.
- →A startup building an AI-powered internal operations tool can fork specific framework examples from this repo as scaffolding, reducing time-to-prototype for workflows like document processing or automated reporting from days to hours.