LangGraph
LangChain's graph-based framework for building stateful multi-agent applications.
LangGraph is LangChain's graph-based framework for building stateful multi-agent applications. Uses a graph-based architecture with nodes and edges to define stateful agent workflows.
About LangGraph
LangGraph is a framework from LangChain for building stateful, multi-agent applications using a graph of nodes and edges.
Its edge is the graph model itself: you define agent workflows as nodes and edges, and it handles state persistence and checkpointing so long-running executions can pause and resume. It is open source and available in both Python and JavaScript/TypeScript, and it plugs into the wider LangChain ecosystem of models, tools, and retrievers.
It fits developers already thinking in terms of explicit agent workflows and comfortable with graph-based programming. It is a poor fit for beginners, since the graph concepts add a learning curve; note too that advanced deployment via LangGraph Platform needs a paid subscription, and debugging complex multi-agent graphs is hard without separate observability tooling.
Among agent frameworks it is the graph-structured, LangChain-native option, trading a steeper concept model for explicit control over state and flow.
Sources: this listing
What it does well
- Uses a graph-based architecture with nodes and edges to define stateful agent workflows.
- Provides built-in state persistence and checkpointing for long-running agent executions.
- Open source framework available in both Python and JavaScript/TypeScript.
- Integrates with the broader LangChain ecosystem including models, tools, and retrievers.
Where it falls short
- Requires understanding of graph-based programming concepts, which adds complexity for beginners.
- Advanced deployment features such as LangGraph Platform require a paid subscription.
- Debugging complex multi-agent graphs can be challenging without dedicated observability tooling.
Tagged
- Self-hostable
- Supports Claude
- Supports GPT
- Supports Gemini
- CLI
- Agentic Mode
- Freemium
- Open Source
Compared with similar things
Picked by shared tags inside the AI Agents (non-coding).
- 01Freemium →LangChain
Most-used framework for building LLM applications with retrieval, agents, and chains.
- 02Freemium →n8n
Open-source workflow automation with native LLM nodes — self-host on your own infrastructure.
- 03Freemium →LlamaIndex
Data framework for connecting LLMs to private data with chunking, indexing, and retrieval primitives.
- 04Freemium →CrewAI
Open-source framework for orchestrating role-playing multi-agent teams in Python.
- 05Freemium →Agno
Lightweight Python framework for building agents with memory, knowledge, and tool-use, formerly Phidata.
- 06Freemium →Skyvern
LLM-powered browser automation that handles forms, captchas, and multi-page flows reliably.
Related reading
- What Is an AI Agent Harness? The Runtime That Turns an LLM Into an Agent
A harness is the runtime wrapper that turns a bare language model into an agent — the layer that runs tools, holds memory, assembles context, and enforces limits. The model does the reasoning; the harness does everything the model can't do on its own. It's the part that decides whether you shipped a chatbot or a real agent — and it's why the same model feels brilliant in one tool and useless in another.
Read guide → - Claude Code Memory
Claude Code has built-in memory — a CLAUDE.md file it reads each session — but it only holds short, hand-written notes. To make it understand a large codebase or docs set, you add a second brain: turn the repo into a knowledge graph, fold that into an Obsidian vault, and let the agent query the map instead of re-reading every file.
Read guide → - How to Do Your Own SEO with Claude Code
Claude Code can do most of your SEO — build a crawlable static site, write and optimize pages, fix the technical layer, even bottle the whole workflow into a reusable skill. What it can't do is invent authority or pick keywords, and if you let it generate 10,000 pages you'll get de-indexed, not ranked. Here's the honest, hands-on version for a maker whose site shipped last week.
Read guide →
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</a>Frequently asked questions
- What is LangGraph?
- LangGraph is LangChain's graph-based framework for building stateful multi-agent applications.
- Is LangGraph free?
- LangGraph offers a free tier and paid plans with higher limits or premium features.
- What platforms does LangGraph support?
- LangGraph runs on mac, win, linux, cli.
- What category does LangGraph belong to?
- LangGraph is in the AI Agents (non-coding) category — Autonomous agents for research, customer support, sales, scheduling, and other non-coding tasks.
- What are the downsides of LangGraph?
- Requires understanding of graph-based programming concepts, which adds complexity for beginners. Advanced deployment features such as LangGraph Platform require a paid subscription. Debugging complex multi-agent graphs can be challenging without dedicated observability tooling.