Updated October 2026 · 8 min read
AI agent frameworks compared: which one should you use?
LangGraph, CrewAI, OpenAI Agents SDK, Microsoft Agent Framework, n8n… there are more agent frameworks than ever, and most comparisons stop at a feature list. Here you answer 4 questions and get the framework that fits you, plus a side-by-side table of the 9 that matter in 2026.
An AI agent framework gives you the building blocks for agents: model calls, tools, memory, hand-offs and guardrails. No code? Start with n8n. Python and a team of agents? CrewAI. Complex flows with branches and state? LangGraph. A light, quick start? OpenAI Agents SDK. .NET or Azure? Microsoft Agent Framework. TypeScript? Mastra. The framework matters less than shipping an agent that does a real job.
Framework picker: 4 questions
Tap one answer per question. Your recommendation appears as soon as you're done.
The 9 AI agent frameworks side by side
What each one is good at, in plain English. Names link to the official project page, so you can check the latest details yourself.
| Framework | Languages | Best for | Style |
|---|---|---|---|
| LangGraph | Python, JS/TS | Complex flows with branches, loops, state and human approval steps | Graph of steps (by LangChain) |
| CrewAI | Python | Teams of agents with roles (researcher, writer, checker) | Role-based crews |
| OpenAI Agents SDK | Python, TS | A light start: agents, tools, hand-offs and guardrails with little code | Minimal building blocks |
| Microsoft Agent Framework | Python, .NET | Companies on Azure / .NET; brings AutoGen and Semantic Kernel ideas together | Agents + workflows |
| Google ADK | Python (+ more) | Code-first agents with built-in evaluation, close to Google Cloud and Gemini | Agent Development Kit |
| LlamaIndex | Python, TS | Agents that answer from your own documents and data | Data + workflows |
| Pydantic AI | Python | Developers who want typed, validated, testable agent output | Type-safe Python |
| Mastra | TypeScript | JS/TS developers building agents into web apps | TS agents + workflows |
| n8n | No code (optional JS/Python) | Business agents wired to WhatsApp, CRM, calendar and email without coding | Visual workflow builder |
Frameworks change fast: always check the project page for the current features and licence. Most of them work with several model providers. The patterns behind team setups are explained in multi-agent systems.
Not sure yet? The free training shows a full agent build without picking a heavy framework →
How to choose: 4 things that actually matter
Feature lists look alike. These four questions decide whether you ship or get stuck.
⌨️ Do you code?
If not, a visual builder gets you to a working agent in days. Code frameworks pay off when you need custom logic.
🧩 One agent or a team?
Most business jobs need one good agent with tools. Teams (CrewAI, LangGraph) help when the job has clearly separate roles.
🔀 How much control?
Approval steps, retries and exact routing? A graph (LangGraph) or workflow gives you that. Simple jobs don't need it.
🚀 Who keeps it running?
Hosting, logs and monitoring matter more than the framework. See AI agent infrastructure.
Go deeper: the full guide series
Each guide covers one part of building and selling agents, with its own interactive demo.
What are AI agents?
Start here: the 4-step loop and a quiz.
Types of AI agents
All 5 types answer the same message.
Multi-agent systems
Watch a team of agents handle one lead.
How to build AI agents
Plan your first agent step by step.
AI agent infrastructure
The stack that keeps agents running.
20 AI agent examples
Real agents by industry.
Start an AI automation agency
Turn agents into a monthly service.
Ways to make money with AI
Compare the realistic options.
AI agent pricing
What agents cost and what to charge.
Free training →
Watch an agent being built and sold, start to finish.
What a working agent is worth to a business
Clients don't buy LangGraph or n8n. They buy an agent that answers, books and follows up every day, usually as a setup fee plus a monthly fee for hosting, monitoring and improving. Play with the numbers:
Example math before costs (model usage, tools, hosting, your time). An example, not a promise: your niche, price and delivery decide what you earn.
The free training shows how to build an agent and sell it as a monthly offer →
Next read: AI agent pricing and what to charge · multi-agent systems explained · how to build AI agents · how to start an AI automation agency
Skip the framework rabbit hole: watch an agent built and sold
Free training, in English, about 45–60 minutes: we build an agent that takes real actions for a business, then show how to package it and charge monthly for it. No coding background needed.
Watch the free training →Free · no credit card
Questions
What is an AI agent framework?
A library or platform with the building blocks for agents: model calls, tools, memory and state, hand-offs between agents and guardrails. New to agents? Read what AI agents are first.
Which AI agent framework is best?
None for everyone. LangGraph for complex flows, CrewAI for role-based teams in Python, OpenAI Agents SDK for a light start, Microsoft Agent Framework for .NET/Azure, Mastra for TypeScript, n8n for no code. Use the picker above.
Do I need to code to build AI agents?
No. Visual tools such as n8n let you build agents with tools and memory by connecting blocks. Code gives more control when you need it.
What happened to AutoGen and Semantic Kernel?
Microsoft brought their ideas together in Microsoft Agent Framework (Python and .NET). Check Microsoft's documentation for the current status of the older projects.
Which framework should I use for client work?
The one you can build, host and maintain fastest. Clients pay for a working agent and monthly care, not for the framework name.