vectrade-examples/
├── python/
│   ├── quickstart.py          # First API call
│   ├── streaming_ai.py        # Stream AI analysis
│   ├── portfolio_tracker.py   # Live portfolio dashboard
│   ├── screener.py            # Custom stock screener
│   └── webhook_server.py      # Flask webhook receiver
├── typescript/
│   ├── quickstart.ts          # First API call
│   ├── edge-function.ts       # Vercel Edge streaming
│   ├── discord-bot.ts         # Discord price alerts
│   └── ai-agent.ts            # AI agent with tools
├── curl/
│   └── examples.sh            # Raw HTTP examples
└── notebooks/
    ├── technical_analysis.ipynb
    └── earnings_calendar.ipynb

from vectrade import VecTrade

client = VecTrade()

# Get a real-time quote
quote = client.quotes.get("AAPL")
print(f"{quote.symbol}: ${quote.price:.2f} ({quote.change_pct:+.2f}%)")

# Batch multiple tickers
batch = client.quotes.batch(["AAPL", "GOOGL", "MSFT", "NVDA"])
for q in batch:
    print(f"  {q.symbol}: ${q.price:.2f}")

# AI analysis with streaming
for chunk in client.ai.stream("What's the bull case for NVDA?"):
    print(chunk.text, end="", flush=True)

import { VecTrade } from "@vectrade/sdk";

const client = new VecTrade();

// Real-time quote
const quote = await client.quotes.get("AAPL");
console.log(`${quote.symbol}: $${quote.price}`);

// Screen for undervalued large-caps
const results = await client.screener.screen({
  marketCap: { min: 10_000_000_000 },
  pe: { max: 15 },
  sector: "Technology",
});

for (const stock of results) {
  console.log(`${stock.symbol} — P/E: ${stock.pe}, Market Cap: $${stock.marketCap}B`);
}

import { createVecTrade } from "@vectrade/ai-provider";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const vt = createVecTrade();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools: vt.tools(),
  maxSteps: 5,
  prompt: "Compare AAPL and MSFT fundamentals. Which is better value?",
});

console.log(text);

{
  "mcpServers": {
    "vectrade": {
      "command": "npx",
      "args": ["-y", "@vectrade/mcp-server"],
      "env": { "VECTRADE_API_KEY": "vq_live_..." }
    }
  }
}

from flask import Flask, request
from vectrade import verify_webhook

app = Flask(__name__)
WEBHOOK_SECRET = "whsec_..."

@app.route("/webhook", methods=["POST"])
def handle():
    event = verify_webhook(
        payload=request.data,
        headers=request.headers,
        secret=WEBHOOK_SECRET,
    )

    if event.type == "price_alert.triggered":
        print(f"🚨 {event.data.symbol} hit ${event.data.price}")

    return "", 200

# Technical analysis notebook
from vectrade import VecTrade
import pandas as pd

client = VecTrade()
technicals = client.technicals.get("AAPL", indicators=["RSI", "MACD", "BB"])

df = pd.DataFrame({
    "RSI": [technicals.rsi.value],
    "MACD": [technicals.macd.value],
    "Signal": [technicals.macd.signal],
    "BB Upper": [technicals.bollinger.upper],
    "BB Lower": [technicals.bollinger.lower],
})
df.style.highlight_max(axis=1)

git clone https://github.com/VecTrade-io/vectrade-examples.git
cd vectrade-examples

# Python
pip install vectrade
python python/quickstart.py

# TypeScript
npm install
npx tsx typescript/quickstart.ts