// nuxt

Market data for
Nuxt apps.

Use the TickerDB Node.js SDK in Nuxt server routes and API endpoints. Pre-computed financial data with no infrastructure to maintain.

try for free read the docs

// setup

Install the SDK.

Add tickerdb to your Nuxt project. Works with Nuxt server routes and composables.

terminal

npm install tickerdb

Set TICKERDB_KEY in your .env file. The SDK reads it automatically.

// usage

Works where Nuxt runs server-side.

Call the SDK in server API routes and expose data through composables. Data never touches the client bundle.

Server API Route server/api/summary/[ticker].ts

import { TickerDB } from "tickerdb";

const client = new TickerDB(process.env.TICKERDB_KEY);

export default defineEventHandler(async (event) => {
  const ticker = getRouterParam(event, "ticker");
  return await client.summary(ticker);
});

Composable composables/useMarketData.ts

export const useMarketData = (ticker: string) => {
  return useFetch("/api/summary/" + ticker);
};

// 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.

Server API Route server/api/watchlist/changes.ts

import { TickerDB } from "tickerdb";

const client = new TickerDB(process.env.TICKERDB_KEY);

export default defineEventHandler(async () => {
  const changes = await client.watchlist.changes();

  // each change includes from/to transitions
  // e.g. trend: "downtrend" → "uptrend"
  return changes;
});

json

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

// ai integration

Feed an AI agent.

TickerDB's categorical output is designed for LLMs. Feed a summary directly into a prompt — the model already understands terms like "oversold" and "strong_uptrend" without extra context.

Server API Route server/api/briefing/[ticker].ts

import { TickerDB } from "tickerdb";
import Anthropic from "@anthropic-ai/sdk";

const ticker = new TickerDB(process.env.TICKERDB_KEY);
const anthropic = new Anthropic();

export default defineEventHandler(async (event) => {
  const t = getRouterParam(event, "ticker");
  const summary = await ticker.summary(t);

  const message = await anthropic.messages.create({
    model: "claude-sonnet-4-20250514",
    max_tokens: 1024,
    messages: [{
      role: "user",
      content: `Analyze this market data for ${t} and provide a brief:\n${JSON.stringify(summary)}`
    }]
  });

  return { analysis: message.content };
});

// 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"
  }
}