LangGraph

tom@tomrochette.com (Tom Rochette) — Tue, 06 Oct 2026 00:00:00 +0000

LangGraph is LangChain’s MIT-licensed, low-level orchestration runtime for building stateful agents as graphs, with durable execution, streaming, human-in-the-loop interrupts, and persistence as the core primitives.

LangGraph is the most-installed orchestration option in this category at 4.55 million npm downloads a week, and the least orchestration-like: it hands you a state machine instead of a team, and its own documentation treats LangSmith, the commercial layer, as the place where a serious deployment ends up.

What it is
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A Python and JavaScript library from LangChain that builds agents as graphs of steps and model calls coordinated through shared state. The documentation’s pitch is durable execution, real-time streaming, human-in-the-loop interrupts, and persistence, which is the machinery the session-oriented columns in the orchestration matrix implement for you. The core is open source under MIT; LangChain’s commercial LangSmith platform is a separate product the documentation references throughout, and I record no prices for it here. LangGraph shows up in eight other section articles (this category’s feature matrix, the Agno and LangChain notes, and the control-planes coverage among them) without having had a note of its own until now.

Status
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Active and enormous: 42,752 stars, 7,268 forks, and 100+ contributors as of 2026-10-05, with the repository created in August 2023. Release 1.2.13 shipped 2026-10-05 on GitHub and PyPI alike, continuing a 1.2.x line that has run all year. npm @langchain/langgraph served 4,552,953 downloads in the week ending 2026-10-04. For scale: that is more weekly installs than any other column in this matrix by a wide margin, and probably more than the rest of the table combined.

Strengths
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Distribution and ecosystem: 4.5 million installs a week means hiring, examples, and answered questions are not a problem here.
The primitives production agents need (durable execution, interrupts, persistence) are the library’s core, not plugins.
MIT across the core, with a release train that keeps shipping.
Practitioner validation: qodo’s 83-point write-up of building a coding agent on LangGraph is the most substantive engineering discussion in this category outside Scion’s launch thread.

Cautions
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It is not an out-of-the-box coding-team runner: no worktrees, no external-CLI harness driving, no review surface, because you build the team and the matrix’s session columns do the rest.
The documentation’s visible LangSmith upsell blurs the line between the free core and the commercial product exactly where procurement questions start.
Low-level by design: expect to write and own the graph, the state schema, and the failure handling.
820 open issues as of 2026-10-05 against that install base is a small ratio, but the issues that matter to you may sit in the closed-source platform, not the repo.

Pricing
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The open source core is free under MIT. LangChain sells LangSmith separately as the commercial layer for deployment, tracing, and management; I found no price table in the pages I checked this run, so I record none rather than guess.

Compared to
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Agno: the other Python option, with a runtime and a paid control plane attached; choose Agno for a platform you can deploy and bill against, LangGraph for raw graph control you own.
Mastra: the TypeScript sibling with evals and a supported platform; choose Mastra in TypeScript stacks, LangGraph in Python ones.
CrewAI: role-based crews assembled in minutes; choose CrewAI for speed of assembly, LangGraph for control over state, interrupts, and recovery.

Bottom line
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Recommended for Python or TypeScript teams building custom multi-step agents who want durable-execution primitives under an MIT license. Not for engineers who want a dashboard, worktrees, and a review flow around existing coding CLIs, because that is what the rest of this category does.

Changes
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2026-10-06 - Created.

References
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https://api.github.com/repos/langchain-ai/langgraph - stars, forks, open issues, MIT license, and push date as of 2026-10-05
https://docs.langchain.com/oss/python/langgraph/ - durable execution, streaming, human-in-the-loop, persistence, and the LangSmith references throughout
https://api.github.com/repos/langchain-ai/langgraph/releases - release 1.2.13 (2026-10-05) and the cadence behind it
https://api.npmjs.org/downloads/point/last-week/@langchain/langgraph - 4,552,953 downloads in the week ending 2026-10-04
https://pypi.org/pypi/langgraph/json - PyPI version 1.2.13
https://news.ycombinator.com/item?id=43468435 - qodo’s “We chose LangGraph to build our coding agent” at 83 points, the practitioner discussion

agent-framework on tomrochette.com

LangGraph

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agent-framework on tomrochette.com

LangGraph

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