LangGraph
Stateful multi-agent orchestration built on LangChain
LangGraph extends LangChain with stateful, graph-based agent orchestration. It handles complex multi-agent workflows with cycles, branching, and persistent state -- solving the linear chain limitation.
Editor rating is our overall editorial judgment of the tool, out of 5. It is not a test score and not a user-review average. Ratings have not been re-scored since the tool was listed here. The reasons are in Best for and Pros & cons below.
Requires some technical comfort with API keys, command line, or coding. If you're new to AI, start with a chat-based tool first.
Best for
Pros & cons
✓ Pros
✗ What this won't do
Use cases
Multi-agent debate systems
Complex approval workflows
Autonomous research agents
Human-in-the-loop agent systems
Install and set your key
Install with pip install -U langgraph, plus pip install -U langchain for the model helpers. The quickstart uses Claude, so set the ANTHROPIC_API_KEY environment variable.
Define the tools
Write three small tools, add, multiply and divide, and attach them to the model with bind_tools. A tool is a function the model may call.
Wire the graph
Make a StateGraph with an llm_call node and a tool_node, connected so the model can call tools and then answer. Compile it into an agent.
Run it and trace it
Send "Add 3 and 4." with agent.invoke and print each message to watch the steps. To see what happened in a run, trace it with LangSmith.
Compare alternatives
| Tool | Category | Editor rating | Pricing |
|---|---|---|---|
| LangGraph (current) | Agent Framework | 4.5 | Free (open-source) |
| LangChain | Agent Framework | 4.6 | Free (open-source) / LangSmith from $39 mo |
| CrewAI | Agent Framework | 4.5 | Free (open-source) / Enterprise pricing |
| AutoGen | Agent Framework | 4.4 | Free (open-source) |