ai-agent

Build Resilient AI Agents with Langgraphjs

Get a framework for language agents as graphs, ideal for founders building AI-powered tools
intermediate1-2 hours💵 Free (self-hosted)
3,206 stars549 forksTypeScriptGuide quality 9/10Updated 8/14/2026100% free · open source
What it is

Build and manage AI agents as graphs using the Langgraphjs framework.

Real use case example

"A founder wants to create an AI-powered support chat. She sets up an agent using Langgraphjs, connects it to her website's API, and defines conditions for automated responses based on user input. With Langgraphjs, she can update or remove nodes easily, ensuring the chat remains functional and user-friendly."

Best insideClaude DesktopCodex CLI
When to use it
  • When you need to create a conversational AI that can handle complex, open-ended user queries.
  • When you want to build a language model that can learn from and adapt to new data and user interactions.
  • When you're developing a chatbot or voice assistant that requires a high level of contextual understanding and conversational flow.
Ready-to-paste prompt
const { LangGraph } = require('langgraphjs'); const graph = new LangGraph(); graph.addNode({ id: 'hello', text: 'Hello, how are you?' }); graph.addEdge({ from: 'hello', to: 'goodbye', text: 'Goodbye!' });
Saves to your device
Use with Claude
New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

🛠️ Technical setup

Expect 20–40 minutes in a terminal — or let your AI agent drive it.

Try it instantly — no install
Claude Code
mkdir -p ~/.claude/skills/langgraphjs && curl -fsSL https://workflowstacks.com/api/skills/langgraphjs/claude-skill -o ~/.claude/skills/langgraphjs/SKILL.md
Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)
claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

How Build Resilient AI Agents with Langgraphjs works
Codeflow
Free to inspect

Build Resilient AI Agents with Langgraphjs is a very large TypeScript project (~126k lines across 670 code files, plus 444 test files). It is a full software project: use it through its install path rather than reading it end to end. Last commit this month, MIT license, has a test suite.

Size
Very large codebase
~126k lines · 670 code files · days to read — use, don't read
Setup
Developer setup
A real software project. Use it via its install path; don't expect to read it all.
Runs on
Node.js
No API keys detected
TypeScript 98%Svelte 1%
Where to start reading
  1. 1
    README.md
    Start here — what it does and how to install it
  2. 2
    AGENTS.md
    The instructions the AI actually follows
  3. 3
    package.json
    Dependencies and the commands it exposes
  4. 4
    internal/bench/README.md
    Inside internal/ — the main logic begins here
  5. 5
    examples/.gitignore
    A worked example — copy this to get going
What's in each folder
internal/Core code — the actual logic81 files
examples/Examples you can copy389 files
docs/Documentation172 files
libs/Folder1280 files
scripts/Helper scripts2 files
.github/CI / automation (GitHub Actions)15 files
.changeset/Tool / agent settings10 files
.devcontainer/Editor / agent settings1 files
READMEHas testsDocumentedCI checksExamples includedMIT licenseUpdated this month
Quick Actions
Details
Creator
langchain-ai
Language
TypeScript
Category
ai-agent
Published
1/9/2024

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