1
LangGraph
Stateful, graph-based agent runtime from the LangChain team.
Pros
- +Explicit graph control
- +Persistence and time travel
- +Production-ready
Cons
- -Tied to LangChain idioms
- -Verbose for simple flows
Best Agent Frameworks
Agent frameworks orchestrate planning, tool use, memory, and multi-step loops on top of an LLM. They differ in how opinionated they are about graph topology, role assignment, and human-in-the-loop checkpoints.
2
CrewAI
Role-based multi-agent framework focused on team-style collaboration.
Pros
- +Clean role/goal/task model
- +Fast to prototype
- +Strong community
Cons
- -Fewer escape hatches
- -Hidden retries
3
AutoGen
Microsoft's conversational multi-agent framework with code execution.
Pros
- +Mature multi-agent chat
- +Strong code execution
- +Backed by Microsoft Research
Cons
- -Configuration heavy
- -Docs scattered across versions
4
OpenAI Agents SDK
OpenAI's official agents library with handoffs and guardrails.
Pros
- +First-party OpenAI support
- +Tight tracing
- +Simple primitives
Cons
- -OpenAI-centric
- -Newer ecosystem
5
Mastra
TypeScript-first agent framework with workflows, memory, and evals.
Pros
- +TS native
- +Built-in evals
- +Integrates with Vercel AI SDK
Cons
- -Young project
- -Smaller community
Related Terms
Concepts you will run into when working with agent frameworks.
Get Smarter About AI Dev
New tutorials, open-source projects, and deep dives on coding agents - delivered weekly.
One email per weekReal code, not theoryFree forever