Intermediate11 min
Agent Framework Comparison
Comparing LangGraph, CrewAI, AutoGen, and Mastra: features, trade-offs, learning curves, and a decision framework for choosing the right tool for your agent project.
Quick Reference
- →LangGraph: graph-based state machines, fine-grained control, Python/JS, production-ready with checkpointing
- →CrewAI: role-based agents, easiest multi-agent setup, Python, great for prototyping team-of-agents patterns
- →AutoGen: Microsoft's multi-agent conversation framework, Python/.NET, strong on complex multi-agent dialogues
- →Mastra: TypeScript-native agent framework, workflow engine, built-in RAG and memory, designed for Node.js backends
- →No framework: minimal dependencies, full control, best for simple tool-calling loops with one provider
The Framework Landscape
The agent framework space has exploded. Each framework has a different philosophy about how agents should be built, and choosing the wrong one can mean months of fighting the abstraction. This article compares the major options so you can make an informed choice before writing your first line of code.
| Framework | Language | Architecture | Learning Curve | Production Readiness | Best For |
|---|---|---|---|---|---|
| LangGraph | Python, JS/TS | State machine graphs | Medium-High | High — used in production at scale | Complex stateful agents, HITL, checkpointing |
| CrewAI | Python | Role-based agents | Low | Medium — maturing quickly | Multi-agent teams, rapid prototyping |
| AutoGen | Python, .NET | Multi-agent conversations | Medium | Medium — Microsoft-backed | Research, complex agent dialogues |
| Mastra | TypeScript | Workflow engine + agents | Low-Medium | Medium — growing ecosystem | Node.js backends, TypeScript teams |
| Vercel AI SDK | TypeScript | Hooks + streaming | Low | High — Vercel-maintained | Frontend chat UIs, Next.js apps |
| Direct API | Any | Your code | Lowest | You decide | Simple agents, maximum control |