AI agent
LangGraph
Open-source Python framework from LangChain for building long-running, stateful agents as graphs. Its docs list durable execution, human-in-the-loop interrupts, memory and optional deployment on LangSmith.
- Maintainer
- LangChain, Inc. (langchain-ai organisation on GitHub)
- Licence
- MIT (LICENSE file: "MIT License", Copyright (c) 2024 LangChain, Inc.)
- Last release
- langgraph 1.2.12, released 2026-09-21 (the repository also publishes langgraph-cli, langgraph-sdk and checkpoint packages as separate releases; the releases page marks the langgraph-cli tag cli==0.4.32.dev0, 2026-09-23, as Latest)
What it can access
An agent can take actions, not only answer questions, so what it is allowed to do on your behalf matters most. This is what the listing states, based on the sources below. Anavem does not rate it safe or unsafe: check it against what you plan to use it for.
Permissions it asks for
- Runs inside your own Python application; you define the tools your agent uses (the quickstart uses the @tool decorator and model.bind_tools)
- Interrupts can pause a run before a tool call so a person can review or edit it; they need a checkpointer and a thread ID
- Checkpointers persist agent state; the docs say production use should have a persistent, database-backed checkpointer
- Optional tracing to LangSmith when you set LANGSMITH_TRACING=true and an API key
Data it can reach
Docs state: LangGraph is a library that runs wherever you run your Python code, and what an agent can reach depends on the tools you give it. The overview docs state it can be used without LangChain. Persisted state goes to the checkpointer database you configure. LangSmith tracing is described as opt-in via environment variables. LangSmith Deployment options listed in the docs: Cloud (managed by LangChain on AWS and GCP), self-hosted with control plane (your Kubernetes cluster), hybrid (LangChain-managed control plane, your data plane) and standalone server (Docker, Compose or Kubernetes with your own PostgreSQL, Redis and a LangSmith license). (README, docs.langchain.com, 2026-10-03)
How it is installed or connected
From the repository README and the LangGraph overview docs (https://docs.langchain.com/oss/python/langgraph/overview), accessed 2026-10-03:
pip install -U langgraph
The LangGraph quickstart (https://docs.langchain.com/oss/python/langgraph/quickstart) sets an ANTHROPIC_API_KEY environment variable in the shell or a .env file for its example model. A JavaScript/TypeScript library, LangGraph.js, is linked from the README.
Limitations
- The overview calls LangGraph "very low-level, and focused entirely on agent orchestration": you write Python code, define tools and choose a model provider; for prebuilt architectures it points to LangChain agents
- Interrupts and durable resume require a checkpointer and a thread ID in the run configuration
- Hosted deployment goes through LangSmith Deployment; the docs list plan requirements (Plus plan or above for Cloud, Enterprise plan for self-hosted with control plane, your own license for standalone)
- The overview states LangGraph "does not abstract prompts or architecture"
Not sure what to look for? Read what to check before installing.
Quick answers
- Who maintains this AI agent?
- LangChain, Inc. (langchain-ai organisation on GitHub).
- What can it access?
- It asks for: Runs inside your own Python application; you define the tools your agent uses (the quickstart uses the @tool decorator and model.bind_tools), Interrupts can pause a run before a tool call so a person can review or edit it; they need a checkpointer and a thread ID, Checkpointers persist agent state; the docs say production use should have a persistent, database-backed checkpointer, Optional tracing to LangSmith when you set LANGSMITH_TRACING=true and an API key. Docs state: LangGraph is a library that runs wherever you run your Python code, and what an agent can reach depends on the tools you give it. The overview docs state it can be used without LangChain. Persisted state goes to the checkpointer database you configure. LangSmith tracing is described as opt-in via environment variables. LangSmith Deployment options listed in the docs: Cloud (managed by LangChain on AWS and GCP), self-hosted with control plane (your Kubernetes cluster), hybrid (LangChain-managed control plane, your data plane) and standalone server (Docker, Compose or Kubernetes with your own PostgreSQL, Redis and a LangSmith license). (README, docs.langchain.com, 2026-10-03). We do not label anything safe or unsafe; read the official sources before you install.
- What licence does it use?
- MIT (LICENSE file: "MIT License", Copyright (c) 2024 LangChain, Inc.). Check the terms if you plan to use it commercially.
- What are its limitations?
- The overview calls LangGraph "very low-level, and focused entirely on agent orchestration": you write Python code, define tools and choose a model provider; for prebuilt architectures it points to LangChain agents. Interrupts and durable resume require a checkpointer and a thread ID in the run configuration. Hosted deployment goes through LangSmith Deployment; the docs list plan requirements (Plus plan or above for Cloud, Enterprise plan for self-hosted with control plane, your own license for standalone). The overview states LangGraph "does not abstract prompts or architecture".
- When was it last released?
- langgraph 1.2.12, released 2026-09-21 (the repository also publishes langgraph-cli, langgraph-sdk and checkpoint packages as separate releases; the releases page marks the langgraph-cli tag cli==0.4.32.dev0, 2026-09-23, as Latest). Verified Oct 3, 2026.
Sources
- langgraph repository (GitHub)accessed
- langgraph README.mdaccessed
- langgraph LICENSEaccessed
- langgraph releases (GitHub)accessed
- LangGraph overview (LangChain docs)accessed
- LangGraph quickstart (LangChain docs)accessed
- LangGraph interrupts (LangChain docs)accessed
- LangSmith Deployment options (LangChain docs)accessed
Related listings
Other listings in the same category.
OpenHands Agent Canvas
Open-source, self-hosted control center for coding agents. It runs the OpenHands agent or other ACP-compatible agents such as Claude Code and Codex on local, Docker, VM or cloud backends, and can run automations on a schedule or from webhooks.
By OpenHands (OpenHands organisation on GitHub) · Verified Oct 3, 2026
OpenAI Agents SDK (Python)
Open-source Python SDK from OpenAI for multi-agent workflows with tools, handoffs, guardrails, sessions, human-in-the-loop, tracing, realtime and voice agents, and sandbox agents. It supports other model providers.
By OpenAI (openai organisation on GitHub) · Verified Oct 3, 2026
CrewAI
Open-source Python framework for multi-agent workflows. Crews are teams of role-based agents; Flows are event-driven workflows. A separate commercial control plane, CrewAI AMP, adds managed deployment and observability.
By crewAI, Inc. (crewAIInc organisation on GitHub) · Verified Oct 3, 2026
AI tools in AI Automation & Agents
Verified tool profiles in the same category.
Zapier
AI Automation & Agents
Workflow automation connecting apps, with Agents and MCP, billed per task
Relevance AI
AI Automation & Agents
Platform for building AI agents and tools, billed in Actions and Vendor Credits
n8n
AI Automation & Agents
Workflow and AI agent platform, hosted by n8n or self-hosted, billed per execution
Make
AI Automation & Agents
Visual automation platform for scenarios and AI agents, billed in credits