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Langgraphjs

Framework to build resilient language agents as graphs.

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Claude CodeCursorWindsurfVS CodeDeveloper tool

About

🦜🕸️LangGraph.js

[](https://langchain-ai.github.io/langgraphjs/)

](https://www.npmjs.com/package/@langchain/langgraph) [

!NOTE] Looking for the Python version? See the [Python repo and the Python docs.

LangGraph — used by Replit, Uber, LinkedIn, GitLab and more — is a low-level orchestration framework for building controllable agents. While langchain provides integrations and composable components to streamline LLM application development, the LangGraph library enables agent orchestration — offering customizable architectures, long-term memory, and human-in-the-loop to reliably handle complex tasks.

bash
npm install @langchain/langgraph @langchain/core

To learn more about how to use LangGraph, check out the docs. We show a simple example below of how to create a ReAct agent.

ts
// npm install @langchain-anthropic
import { createReactAgent, tool } from "langchain";
import { ChatAnthropic } from "@langchain/anthropic";

import { z } from "zod";

const search = tool(
  async ({ query }) => {
    if (
      query.toLowerCase().includes("sf") ||
      query.toLowerCase().includes("san francisco")
    ) {
      return "It's 60 degrees and foggy.";
    }
    return "It's 90 degrees and sunny.";
  },
  {
    name: "search",
    description: "Call to surf the web.",
    schema: z.object({
      query: z.string().describe("The query to use in your search."),
    }),
  }
);

const model = new ChatAnthropic({
  model: "claude-3-7-sonnet-latest",
});

const agent = createReactAgent({
  llm: model,
  tools: [search],
});

const result = await agent.invoke({
  messages: [
    {
      role: "user",
      content: "what is the weather in sf",
    },
  ],
});

Full-stack Quickstart

Get started quickly by building a full-stack LangGraph application using the `create-agent-chat-app` CLI:

bash
npx create-agent-chat-app@latest

The CLI sets up a chat interface and helps you configure your application, including:

  • 🧠 Choice of 4 prebuilt agents (ReAct, Memory, Research, Retrieval)
  • 🌐 Frontend framework (Next.js or Vite)
  • 📦 Package manager (npm, yarn, or pnpm)

Why use LangGraph?

LangGraph is built for developers who want to build powerful, adaptable AI agents. Developers choose LangGraph for:

Don't lose this

Three weeks from now, you'll want Langgraphjs again. Will you remember where to find it?

Save it to your library and the next time you need Langgraphjs, it’s one tap away — from any AI app you use. Group it into a bench with the rest of the team for that kind of task and you can pull the whole stack at once.

⚡ Pro tip for geeks: add a-gnt 🤵🏻‍♂️ as a custom connector in Claude or a custom GPT in ChatGPT — one click and your library is right there in the chat. Or, if you’re in an editor, install the a-gnt MCP server and say “use my [bench name]” in Claude Code, Cursor, VS Code, or Windsurf.

🤵🏻‍♂️

a-gnt's Take

Our honest review

Framework to build resilient language agents as graphs. Best for anyone looking to make their AI assistant more capable in automation. It's completely free and works across most major AI apps. This one just landed in the catalog — worth trying while it's fresh.

Tips for getting started

1

Tap "Get" above, pick your AI app, and follow the steps. Most installs take under 30 seconds.

What's New

Version 1.0.06 days ago

Imported from GitHub

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