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Abhishek Chauhan
Abhishek Chauhan

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I Built a Multi-Agent Starter Kit with LangGraph — 6 Patterns, 5 Providers, One Command

#ai #langchain #programming

If you've built more than one LangGraph project, you know the drill. Supervisor setup. Provider config. Handoff tools. Persistence. Streaming endpoint. Same boilerplate, different repo.

So I stopped rewriting it and packaged the whole thing.

LangGraph Starter Kit 

npx create-langgraph-app
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Interactive CLI. Pick your provider, pick your patterns, get a project that runs.

Or clone the full kit with everything included.

6 Patterns

Each one is a standalone app you can use, modify, or delete:

  • Supervisor — central coordinator routes tasks to worker agents
  • Swarm — agents hand off to each other with transfer tools, no central brain
  • Human-in-the-Loop — graph pauses for approval before destructive actions
  • Structured Output — typed JSON responses validated by Zod
  • Research Agent — web search + scraping, supervisor coordinates a researcher and writer
  • RAG — in-memory vector store, semantic retrieval, no external DB

5 Providers 

LLM_PROVIDER=anthropic
ANTHROPIC_API_KEY=sk-ant-...
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Two lines. Done.

OpenAI, Anthropic, Google, Groq, Ollama (local). Each has a sensible default model. Override with LLM_MODEL if you want.

Extending It 

export function createMyApp() {
  const agent = makeAgent({
    name: "my_agent",
    llm,
    tools: [/* your tools */],
    system: "You are a helpful assistant.",
  });

  return makeSupervisor({
    agents: [agent],
    llm,
    outputMode: "last_message",
    supervisorName: "my_supervisor",
  });
}
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Register in the server. New endpoint with streaming, threads, and persistence.

Also Ships With

  • MCP tool integration (stdio + HTTP)
  • SSE streaming on every endpoint
  • LangGraph Studio config
  • LangSmith tracing (one env var)
  • Docker Compose with Postgres
  • 25+ tests, GitHub Actions CI
  • Railway + Render deploy configs

Get Started 

npx create-langgraph-app
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Or:

git clone https://github.com/ac12644/langgraph-starter-kit.git
cd langgraph-starter-kit
npm install && cp .env.example .env
npm run dev
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GitHub logo ac12644 / langgraph-starter-kit

Boilerplate for building multi-agent AI systems with LangGraph. Includes Swarm and Supervisor patterns, memory, tools, and HTTP API out of the box.

LangGraph Starter Kit


The fastest way to build production-ready multi-agent apps with LangGraph


6 patterns. 5 providers. One command.

CI License TypeScript LangGraph Stars

Quick Start • Patterns • Providers • API • Contributing

Why This Exists

Building multi-agent systems with LangGraph means writing the same boilerplate over and over — setting up supervisors, wiring handoff tools, configuring providers, adding persistence. This starter kit gives you all of that out of the box so you can focus on your agent logic, not infrastructure.

npx create-langgraph-app
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What you get:

  • Pick your LLM provider (OpenAI, Anthropic, Google, Groq, or local Ollama)
  • Choose which agent patterns you need
  • Get a ready-to-run project with tests, types, and a Fastify server

Or clone the full kit with all 6 patterns included.

Architecture

              ┌─────────────────────────────────────────────┐
              │             LangGraph Starter Kit            │
              └──────────────────┬──────────────────────────┘
                                 │
              ┌──────────────────┼──────────────────────┐
              ▼                  ▼                       ▼
       ┌─────────────┐   ┌─────────────┐        ┌─────────────┐
       │  CLI Demo    │   │ HTTP Server │        │  LangGraph  │
       │  npm
…
View on GitHub

Apache 2.0. PRs welcome.

What are you building with LangGraph? Curious what patterns people are reaching for.

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