OpenClaw vs AutoGen vs LangGraph vs browser-use vs crewAI: AI Agent Frameworks Compared (2026)
Direct answer: The five leading open-source AI agent frameworks in 2026, with GitHub stars verified 2026-08-13: OpenClaw (386,079 ★) for a personal assistant that spans terminal, browser, and messaging; browser-use (108,966 ★, MIT) for browser automation; AutoGen (60,388 ★, CC-BY-4.0) for multi-agent conversations from Microsoft; LangGraph (39,551 ★, MIT) for stateful, low-level agent graphs; and crewAI (57,000 ★, MIT) for role-based agent crews. Match the framework to the job: a general assistant means OpenClaw, a browser task runner means browser-use, research pipelines mean AutoGen, fine-grained control means LangGraph, and role-played teams mean crewAI.
What these frameworks are
All five let you build software that uses LLMs to take actions, but they sit at different levels. OpenClaw is a full personal agent you install and talk to. browser-use is a library that connects an agent to a real browser. AutoGen, LangGraph, and crewAI are programming frameworks where you write code to define agents, tools, and conversations.
The comparison (verified 2026-08-13)
| Framework | Stars (GitHub) | License | Level | Best for |
|---|---|---|---|---|
| OpenClaw | 386,079 | Other | End-user agent | Personal assistant across terminal/browser/messaging |
| browser-use | 108,966 | MIT | Library | Agent web automation |
| AutoGen | 60,388 | CC-BY-4.0 | Framework | Multi-agent research conversations |
| crewAI | 57,000 | MIT | Framework | Role-based agent teams |
| LangGraph | 39,551 | MIT | Framework | Stateful graphs, fine-grained control |
OpenClaw (386,079 ★)
OpenClaw is the most-starred agent project on GitHub. It is a personal AI assistant that runs on any OS, drives a terminal and browser, connects to messaging platforms, and keeps memory across sessions. You install it once and give it tasks directly, for example "research this, then write a report." It is the closest thing to a general-purpose agent you can self-host. The trade-off is that you live inside OpenClaw's workflow instead of assembling your own.
browser-use (108,966 ★, MIT)
browser-use makes websites accessible to AI agents. It takes a task in natural language and drives a real browser through an LLM loop: clicking, typing, extracting. It is a Python library you drop into your own agent, which is why it pairs well with OpenClaw or LangGraph for anything web-shaped: form filling, data collection, end-to-end testing. The MIT license makes it safe for commercial embedding.
AutoGen (60,388 ★, CC-BY-4.0)
AutoGen, from Microsoft, is a programming framework for agentic AI built around conversations. Agents talk to each other and to tools to solve a task. Its strength is research-style work: one agent plans, another searches, another critiques, and the conversation converges on a result. The CC-BY-4.0 license is worth checking before shipping a commercial product. It allows use but carries attribution terms.
crewAI (57,000 ★, MIT)
crewAI is the role-playing framework. You define a crew of agents with roles such as "researcher," "writer," and "reviewer" that collaborate on a goal, with built-in task management. It is the fastest way to get a multi-agent team working on structured, repeatable workflows. It is MIT licensed and easy to learn, but less flexible than LangGraph when you need unusual control flow.
LangGraph (39,551 ★, MIT)
LangGraph is the low-level option. Agents are explicit state machines, graphs where you control every node, edge, and checkpoint. It comes from the LangChain team, works with any model, and gives you production-grade persistence and human-in-the-loop control. The cost is complexity: you write more code, but you get exactly the behavior you specified. Choose it when the other frameworks' assumptions do not fit.
How to decide
- Building a general assistant you will talk to daily: OpenClaw (386,079 ★)
- Automating browser tasks inside your own code: browser-use (108,966 ★, MIT)
- Research pipelines with multiple agents debating a problem: AutoGen (60,388 ★)
- Structured role-based teams for repeatable work: crewAI (57,000 ★, MIT)
- Full control over agent state and flow: LangGraph (39,551 ★, MIT)
The honest part
Stars do not tell you which framework fits. They tell you which has the biggest community. OpenClaw's 386k stars reflect its status as the default personal agent; LangGraph's 39k reflect a narrower, more technical audience, not a worse project. The real question is whether you want to install an agent (OpenClaw) or build one (the frameworks). Most people start with OpenClaw and add browser-use or LangGraph when they need something specific underneath.
FAQ
Do I need to know how to code? For OpenClaw, no. It is an assistant you install and talk to. browser-use, AutoGen, crewAI, and LangGraph are libraries: you write Python.
Can these run on my own hardware? Yes. All five run locally or on your own server, and all work with local models (Ollama, vLLM) through OpenAI-compatible APIs.
Which is best for web automation? browser-use is the dedicated option and pairs with any of the others. OpenClaw also drives a browser out of the box.
How were stars verified? GitHub API, 2026-08-13, official repositories: OpenClaw 386,079 ★, browser-use 108,966 ★, AutoGen 60,388 ★, crewAI 57,000 ★, LangGraph 39,551 ★.
Summary
Verified 2026-08-13: OpenClaw (386,079 ★) is the install-and-go personal agent; browser-use (108,966 ★, MIT) adds browser automation to your code; AutoGen (60,388 ★) and crewAI (57,000 ★, MIT) ship multi-agent teams fast; LangGraph (39,551 ★, MIT) gives you full control. Match the framework to the job, not to the star count. Browse the full 461-tool catalog at [ylyvip.net/tools](/tools).