Feature
| AI Agent Framework | Best Use Cases |
|---|---|
| MetaGPT | Collaborative software development, website and game development, rapid prototyping of digital products |
| SuperAGI | Sales and marketing automation, support bots, agent-based task delegation in enterprise functions |
| Microsoft AutoGen | Enterprise software development, scalable agent-based applications, enterprise software development |
| LangChain | Conversational agents (chatbots, support bots), document processing and summarization, RAG-based search systems |
| AutoGPT | Web research and report generation, small business and solo user automation, personal assistants |
| BabyAGI | Personal productivity agents, task list generation and dynamic prioritization, research automation |
| CrewAI | Multi-agent orchestration, content creation at scale, collaborative problem solving |
AI agent frameworks are pre-built sets of components that allow you to snap together agents without coding every process yourself. These agents can help you build tools faster, making sure they're all similar, scalable and capable of adding features you might not have the time or skills to code yourself.
AI agents have huge potential. And AI agent frameworks can help you build them. Ready to try it?
MetaGPT
Deep Wisdom's MetaGPT is another multi-agent framework that helps you build collaborative teams of agents to enable complex problem solving and software development. It can help create websites, software, games and more.
Introducing MGX (MetaGPT X), The First AI Dev Team.
— MetaGPT (@MetaGPT_) February 19, 2025
· Chat with the AI team leader, product manager, architect, engineer, and data analyst 24/7 to create websites, blogs, shops, analytics, games, or anything else you can imagine.
· Build, deploy, share, and remix various… pic.twitter.com/fD4d49fpnI
Build agents to do specific development jobs — project manager, engineer, reviewer — and create a development team made up of AI agents. The team will follow a structured workflow, working together to create software, gather data, write code and run tests. The agents communicate with each other, refine their tasks and maintain a continuous workflow. It is very customizable, but complicated to set up, power-hungry and still evolving.
SuperAGI
An open-source framework, SuperAGI is designed to build autonomous agents that help with sales, marketing, software development and support. The company goal is to empower everyone with super intelligence.
This framework excels at planning and execution due to its persistent memory retention, and it allows for team-based AI problem solving because the agents can interact among themselves. It connects to APIs, databases and external tools so that you can build out a high-functioning agent or a team of agents. One consideration to keep in mind, however, is that a team of interacting agents will require significant compute power to operate.
Related Article: Is Your Data Good Enough to Power AI Agents?
Microsoft AutoGen
If you like the idea of an open-source agent framework deployed into your business that's backed by Microsoft and able to work with other enterprise tools, Microsoft AutoGen might be your answer. The latest version, AutoGen v0.4, has a robust, asynchronous and event-driven architecture, which enables a broad range of skills, flexible collaboration patterns and reusable components.
🌻Serving AutoGen Agents@wronkiew created a way for users to interact with AutoGen 0.4 agents using a familiar chat interface such as @OpenWebUI
— AutoGen (@pyautogen) March 17, 2025
Checkout this new open source AutoGen sample below. https://t.co/ECwBAjJzGB
Another multi-agent system, it allows you to deploy a team of agents to help you build software, each one taking on a job much like those you would assign to a human development team. One agent might code while another debugs, for example. Those agents are adaptive, assigning tasks dynamically. It taps GPT-based LLMs as well as other models and is a powerful, flexible and customizable system. It is not simple to set up, though, and can be computationally expensive.
LangChain
LangChain is a go-to tool for developers looking to build agents that are powered by large language models (LLMs). The company is “on a mission to make it easy to build the LLM apps of tomorrow, today.” You might use it to build chatbots for customer support or other purposes, create autonomous agents or tools for processing and summarizing long documents. You can use it to build, deploy, monitor and maintain your agents.
It has modular components — memory, tools and chains — that work and integrate with lots of LLMs, including OpenAI, Anthropic, Cohere. It is also capable of reasoning, searching, doing calculations and executing API calls. It has support for retrieval-augmented generation (RAG) and knowledge bases.
If you are new to this idea, the site has deep resources for learning how to work with agent frameworks and LangChain, in particular. It offers lots of integrations to connect your agents to the other tools you use.
AutoGPT
Claiming to “level the playing field by making AI universally accessible,” AutoGPT, built on ChatGPT-4, offers a set of tools that brings advanced AI into striking distance for everyone, even those without the technical skills to build intelligent AI agents.
🚀 Introducing the AutoGPT Platform! Create, deploy, and manage continuous #AIAgents that work tirelessly for you.
— AutoGPT (@Auto_GPT) September 24, 2024
Experience the future of AI automation today 🔮
Learn more ➡️ https://t.co/fNVFqZ7EVq pic.twitter.com/i1Wpaugfnw
This tool lets you easily create autonomous AI agents that can plan and execute multi-step tasks, as well as use LLMs to break tasks into subtasks and execute them. The agents you build can browse the web, use APIs, interact with long documents or files and create content. Whether you are looking for tools to speed your research, to automate business processes or even a personal AI assistant, it can help you build clever AI agents that require a minimum of human oversight.
Since this is an open-source tool, it gets frequent updates from the community.
BabyAGI
BabyAGI is designed to mimic the way humans think and learn. It was created by Yohei Nakajima, a venture capitalist and AI enthusiast who set out to create an agent that could replicate his own workflow.
This tool integrates niftily with OpenAI's GPT models and is clever in that it can continuously refine its task list, prioritizing and reorganizing tasks and steps based on previous results. It requires little human intervention, which makes it perfect for streamlining workflows. You can also build it out with additional APIs — databases or web scraping tools for instance — to boost your data collection.
Related Article: The AI Agent Explosion: Unexpected Challenges Just Over the Horizon
CrewAI
The premise of CrewAI is that it builds teams of AI agents that work together to accomplish complex tasks. You give each agent a job — researcher, writer, analyst — and create a little team of intelligent agents to do your work for you. It can create sophisticated workflows and would be of terrific assistance to a research team or content creation crew.
Effortlessly trace and monitor multi-agent LLM applications!
— Akshay 🚀 (@akshay_pachaar) March 21, 2025
With just two lines of code, Opik tracks everything happening inside your AI application, including costs. See the CrewAI example below.
100% open-source, self-hosted. pic.twitter.com/pp95bsVkUo
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This solution is more complex to set up than some of the simpler agents here. But, when mastered, it has great potential. It can work with any LLM, has a plethora of integrations and has been adopted by some big names in tech, like Oracle, Deloitte, Accenture and more.
