LangGraph
Open-source graph framework for durable, stateful AI agents
Overview
LangGraph is LangChain's MIT-licensed framework for building stateful, durable AI agents as graphs — checkpoints, human-in-the-loop interrupts, streaming and time travel — in Python and JavaScript. Managed deployment now runs on LangSmith Deployment, from a free Developer plan to $39 per seat a month for Plus.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 1 Oct 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
- Up to 5k base traces/mo
- 1 seat, community support
- No managed deployment
- Up to 10k base traces/mo
- Unlimited seats
- 1 free Serverless (Small) deployment
- 25 LCU of Fleet usage a month
- Cloud, hybrid or self-hosted
- Custom SSO, ABAC and RBAC
- Support SLA, email and Slack support
What you can produce with LangGraph
- Graph-based agent orchestration with explicit state
- Durable execution with checkpointing and resume
- Human-in-the-loop interrupts mid-run
- Time travel: replay or fork runs from checkpoints
- Python and JavaScript/TypeScript libraries (MIT)
- Managed hosting via LangSmith Deployment
- Streaming of tokens and intermediate steps
LangGraph is the framework to reach for when an agent needs real control flow: explicit state, branching, loops, multi-agent hand-offs, checkpoints that survive failures and human approval steps, in Python or JavaScript, under the permissive MIT licence. Version 1.0 in October 2025 settled the API, and LangChain's $125 million raise gives it a long runway. Managed hosting is now LangSmith Deployment, priced by compute units with a $39-per-seat Plus plan, and it also hosts agents built with other frameworks, which reduces lock-in. Many production stories are LangChain's own case studies, so weigh them accordingly. The explicit graph model takes more setup than lighter agent libraries; for simple tool-calling agents it is overkill, but for complex, long-running agents it is one of the most mature choices.
What we found
LangGraph is LangChain's open-source framework for building agents as graphs: you define nodes, edges and shared state explicitly, which makes branching, loops, multi-agent hand-offs and long-running work predictable rather than left to a prompt. Checkpointing gives it durable execution — a run can pause, survive a failure and resume — along with human-in-the-loop interrupts, streaming of tokens and intermediate steps, and "time travel", replaying or forking a run from any saved checkpoint. It is available for Python and JavaScript under the MIT licence; version 1.0 shipped in October 2025, and 1.2 is current.
Deployment has been reorganised. What used to be the LangGraph Platform is now LangSmith Deployment, which also runs agents built with Google's ADK, CrewAI or Anthropic's Claude Agent SDK, and is billed in compute and storage units rather than node executions. The LangSmith Developer plan is free for one seat with 5,000 traces a month but no managed deployment; Plus costs $39 per seat a month with 10,000 traces, unlimited seats and one free small serverless deployment; Enterprise adds hybrid or self-hosted LangSmith, SSO, fine-grained access control and support SLAs. Start-ups can apply for up to $10,000 in credits.
LangChain, the San Francisco company behind it, raised $125 million at a $1.25 billion valuation in October 2025, led by IVP, and says its libraries see 90 million combined monthly downloads and that 35% of the Fortune 500 use its services. Production stories are mostly published by LangChain itself: Klarna's assistant for 85 million users, which it says cut resolution time by 80%; Replit's multi-agent coding agent; and Uber engineers describing time saved at LangChain's own conference. Elastic has written independently about moving its security features onto LangGraph.
The trade-off is explicitness: LangGraph asks you to model state and flow yourself, which pays off for complex, long-running agents and is overkill for a single tool-calling loop.
Compiled by RECATOOLS from public sources: vendor documentation and pricing, code repositories and published reporting.
About this listing
This entry was compiled from publicly available data including LangGraph's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with LangGraph unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
For the latest details, please refer to LangGraph directly →
Spotted something out of date? Suggest an update →
Alternatives to LangGraph
More in Agents & Automation
