LangGraph

1. Install the CLI

npm install -g swytchcode

irm https://cli.swytchcode.com/install.ps1 | iex

curl -fsSL https://cli.swytchcode.com/install.sh | sh

Use swy as a shorter alias for swytchcode.

2. Install the packages

JavaScript
Python

npm install @swytchcode/runtime @langchain/core langgraph dotenv

pip install swytchcode-runtime langgraph python-dotenv

3. Initialize Swytchcode and fetch a toolkit

swy init
swy get github

swy init creates .swytchcode/ and tooling.json for the project. swy get github downloads the GitHub integration bundle - the schemas that tools.get reads from in the next step.

import 'dotenv/config';
import { Swytchcode } from '@swytchcode/runtime';
import { LangGraphProvider } from '@swytchcode/runtime/providers/langgraph';

const swx = new Swytchcode(new LangGraphProvider());
const tools = await swx.tools.get({ toolkits: ['github'] });

import os
from dotenv import load_dotenv
from swytchcode_runtime import Swytchcode

load_dotenv()

swx = Swytchcode()
tools = swx.tools.get(toolkits=["github"])

print(f"Loaded {len(tools)} tools")

5. Pass them into LangGraph

JavaScript
Python

// Build your graph with the returned tools and let the agent invoke them.
console.log('LangGraph tools ready:', tools.length);

result = swx.tools.execute("github.pull_requests.list", {
    "params": {"state": "open"},
    "Authorization": f"Bearer {os.getenv('GITHUB_TOKEN')}",
})

print(result)

6. Run the file

Save the example as main.js or main.py, then run the matching command:

JavaScript
Python

node main.js

python main.py

This keeps tool execution inside Swytchcode while the workflow graph stays focused on orchestration.

Example projects

Browse all examples →

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