// node.js sdk

TickerDB for Node.js.

Type-safe client for the TickerDB HTTP API. Install, initialize, and start pulling market data in under a minute. Full TypeScript support included.

get api key read the docs

// quick start

Install and call in 30 seconds.

One package. One import. No configuration files, no build steps.

install

// install from npm
npm install tickerdb

typescript

import { TickerDB } from "tickerdb";

const client = new TickerDB("tapi_your_api_key");

// Get a full summary for any ticker
const summary = await client.getSummary("AAPL");
console.log(summary.trend.direction);    // "uptrend"
console.log(summary.momentum.rsi_zone);  // "neutral_high"

view on npm →

// multi-step analysis

Chain calls. Build context.

Pull a summary, check for historical band transitions, then monitor your watchlist for changes. Each method returns typed, categorical data you can branch on directly.

client.getSummary("AAPL")

Full categorical breakdown — trend, momentum, volatility, fundamentals

client.getEvents("AAPL", "rsi_zone", "deep_oversold")

Historical band transitions for RSI entering deep oversold

client.getWatchlistChanges()

State changes across your monitored tickers

// state changes

Track state changes effortlessly.

Most market data APIs return point-in-time snapshots. TickerDB tracks state transitions — your agent sees what changed, not just what is.

typescript

const summary = await client.getSummary("AAPL");

json

{
  "ticker": "AAPL",
  "changes": [
    {
      "field": "rsi_zone",
      "from": "neutral",
      "to": "oversold"
    },
    {
      "field": "trend",
      "from": "uptrend",
      "to": "downtrend"
    }
  ]
}

// what your agent sees

What your agent sees.

Every tool returns categorical facts — not raw OHLCV data. Your agent can branch on "oversold" without needing to know what RSI > 70 means.

json

{
  "ticker": "NVDA",
  "trend": "strong_uptrend",
  "momentum": {
    "rsi_zone": "overbought",
    "macd_signal": "bullish"
  },
  "volatility": "high",
  "fundamentals": {
    "pe_zone": "above_historical_avg",
    "earnings_surprise": "positive"
  }
}