LangGraph
FreemiumBuild stateful, multi-agent systems as controllable graphs.
Published 27 September 2026
Scores
Popularity4/5
A rapidly growing, heavily starred project that has become the execution substrate under LangChain's own agent API, though narrower in direct adoption than the broader LangChain library.
Learning Curve4/5
The graph, typed-state, and checkpointer model is powerful but deliberately low-level, so getting a non-trivial multi-agent graph right takes meaningfully more effort than a batteries-included framework.
Flexibility5/5
Nodes, conditional edges, cycles, and pluggable checkpointers can express essentially any agent control flow, from simple loops to complex multi-agent handoffs.
Performance4/5
Durable execution, persistent state, and horizontally scaling queues on the platform are built for production-grade, long-running agent workloads rather than just prototypes.
Portability5/5
MIT-licensed with Python and JavaScript SDKs and no usage limits, self-hostable and provider-agnostic, so the core runtime carries no lock-in.
About LangGraph
LangGraph is a low-level orchestration framework from LangChain, Inc. for building stateful, controllable agents. Where a simple chain runs top to bottom, LangGraph models an agent's control flow as a StateGraph — nodes connected by direct and conditional edges, with cyclic execution, branching, and a typed state object that flows through every step. A checkpointer persists that state between steps, which is what enables durable execution, retries, human-in-the-loop pauses, and time-travel debugging of past runs.
This is the layer production teams reach for once an agent's logic stops being a straight line — multi-agent handoffs, loops, long-running workflows, and interventions that need to survive process restarts. As of late 2025, LangChain's own high-level create_agent API runs on top of LangGraph's execution engine, so LangGraph increasingly functions as the substrate beneath LangChain rather than a competing choice; it is equally usable standalone by teams who want the graph and state primitives without LangChain's higher-level abstractions. It ships as both a Python and a JavaScript/TypeScript library.
The core library is MIT-licensed and free, with no usage limits. LangChain also offers the LangGraph Platform, a managed runtime that adds a deployment server, one-click deploys, horizontally scaling task queues, and LangGraph Studio for visual debugging — priced separately for teams that want hosted, durable agent infrastructure rather than self-hosting the open-source runtime.
Key Features
- StateGraph model: nodes and edges with cyclic execution and conditional branching
- Durable execution via checkpointers that persist typed state between every step
- Human-in-the-loop pauses, retries, and time-travel debugging of past runs
- Runs the execution engine beneath LangChain's own create_agent API
- Python and JavaScript/TypeScript libraries, MIT-licensed with no usage limits
- Optional LangGraph Platform: managed server, scaling queues, and LangGraph Studio
Pros
- Fine-grained control over agent control flow that linear chains cannot express
- Durable, checkpointed state makes long-running and human-in-the-loop agents production-viable
- Free and MIT-licensed core with no usage restrictions
- Backed by LangChain and increasingly the standard execution layer under it
Cons
- Lower-level and more verbose than higher-level frameworks — more to learn upfront
- Graph, state, and checkpointer concepts add real conceptual overhead for simple agents
- Managed LangGraph Platform is a separate paid product for hosted deployment
- Naming overlaps with visual orchestration tools despite being a code-first SDK
LangGraph Pricing
Freemium- · Free, MIT-licensed Python and JavaScript library with no usage limits
- · Full StateGraph, checkpointing, and durable-execution primitives, self-hosted
- · Managed runtime: deployment server, one-click deploys, scaling task queues, LangGraph Studio
- · Usage-based pricing with a free developer allowance, plus enterprise self-hosting options
Tech Stacks with LangGraph
Python AI Agent
ProjectA code-first AI agent in Python. An agent framework such as LangGraph or Pydantic AI runs the loop, FastAPI serves it, PostgreSQL (your own, Neon, or Supabase) stores its state, and a model such as Claude or OpenAI does the reasoning.
React + Django
ProjectReact frontend with a Django REST API backend, a popular Python full-stack combination.
Vue + FastAPI
ProjectVue.js frontend paired with FastAPI, a fast, async-ready Python API backend.
Tools Related to LangGraph
Integrates with LangGraph(1)
LangGraph agents are debugged in LangSmith's Studio and deployed through LangSmith Deployment, the managed runtime formerly called LangGraph Platform.
Built on (2)
LangGraph is a Python library for building stateful agents as graphs of nodes and edges.
LangGraph.js is LangGraph's JavaScript and TypeScript edition, with the same graph and checkpointing model as the Python library.
Alternatives to LangGraph(8)
Both build multi-agent systems — CrewAI with a high-level role/task model, LangGraph with a low-level state-graph runtime. Competing approaches to orchestrating agents.
Both frameworks let developers hand-build multi-step agent workflows with explicit control flow — LangGraph as a Python state-graph runtime, Mastra as a typed TypeScript workflow engine.
LangChain's create_agent gives a ready-made agent loop built on LangGraph, while LangGraph itself is the lower-level runtime for hand-built graphs with explicit state and branching. Pick LangChain for standard agents, LangGraph for custom control flow.
The OpenAI Agents SDK runs a ready-made agent loop with handoffs between agents; LangGraph makes you define the graph, state, and branching explicitly. Pick the SDK for speed to a working agent, LangGraph for fine control over complex stateful workflows.
The Claude Agent SDK hands control to a proven autonomous loop with subagents and hooks; LangGraph has you lay out each step as an explicit graph with state. Pick the SDK for open-ended tasks on Claude, LangGraph for controlled workflows on any model.
Both are code-first Python agent frameworks; LangGraph focuses on graph-based orchestration, Pydantic AI on type-safe validation. Competing choices for building agents in code.
Vendor
LangChain
Website →Tags
Details
- Maintained
- Yes
- Agent type
- Framework
- Primary language
- Python
- Open source
- Yes
- Hosting
- Self-hosted
- GitHub stars
- 42.2k
- Stars updated
- 2026-09-23