Market data for
Nuxt apps.
Use the TickerAPI Node.js SDK in Nuxt server routes and API endpoints. Pre-computed financial data with no infrastructure to maintain.
Install the SDK.
Add tickerapi to your Nuxt project. Works with Nuxt server routes and composables.
npm install tickerapi Set TICKERAPI_KEY in your .env file. The SDK reads it automatically.
Works where Nuxt runs server-side.
Call the SDK in server API routes and expose data through composables. Data never touches the client bundle.
import { TickerAPI } from "tickerapi"; const client = new TickerAPI(process.env.TICKERAPI_KEY); export default defineEventHandler(async (event) => { const ticker = getRouterParam(event, "ticker"); return await client.summary(ticker); });
export const useMarketData = (ticker: string) => { return useFetch("/api/summary/" + ticker); };
Track state changes effortlessly.
Most market data APIs return point-in-time snapshots. TickerAPI tracks state transitions — your agent sees what changed, not just what is.
import { TickerAPI } from "tickerapi"; const client = new TickerAPI(process.env.TICKERAPI_KEY); export default defineEventHandler(async () => { const changes = await client.watchlist.changes(); // each change includes from/to transitions // e.g. trend: "downtrend" → "uptrend" return changes; });
{ "ticker": "AAPL", "changes": [ { "field": "rsi_zone", "from": "neutral", "to": "oversold" }, { "field": "trend", "from": "uptrend", "to": "downtrend" } ] }
Feed an AI agent.
TickerAPI'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.
import { TickerAPI } from "tickerapi"; import Anthropic from "@anthropic-ai/sdk"; const ticker = new TickerAPI(process.env.TICKERAPI_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.
Every tool returns categorical facts — not raw OHLCV data. Your agent can branch on "oversold" without needing to know what RSI > 70 means.
{ "ticker": "NVDA", "trend": "strong_uptrend", "momentum": { "rsi_zone": "overbought", "macd_signal": "bullish" }, "volatility": "high", "fundamentals": { "pe_zone": "above_historical_avg", "earnings_surprise": "positive" } }
What you can call.
Every tool returns categorical, pre-computed data. Your agent gets facts it can reason about immediately.
Full factual snapshot for a single asset — trend, momentum, fundamentals, support/resistance.
Side-by-side technical and fundamental comparison of two or more tickers.
Browse all supported tickers with filtering and search.
List all valid sector values with asset counts for scan filtering.
Live summary data for all tickers in your saved watchlist.
Field-level diffs for your watchlist since the last pipeline run.
Add tickers to your persistent watchlist.
Remove tickers from your watchlist.
Assets in confirmed oversold conditions across multiple indicators.
Assets in overbought RSI conditions with severity rankings.
Momentum breakouts with volume confirmation.
Volume anomalies and accumulation patterns.
Historically undervalued or overvalued assets based on fundamental metrics.
Notable insider buying and selling activity.
Your plan tier, rate limits, and current API usage.
Register a webhook URL for watchlist change notifications.
List your registered webhook URLs.
Remove a registered webhook.
Built for how agents consume data.
Categorical data, less prompt engineering
Responses like "rsi_zone": "oversold" are already in a format the model understands. No need to explain what RSI > 70 means.
Compact responses
Tool-call context windows are limited. TickerAPI responses are a fraction of the tokens you'd need to pass raw OHLCV data.
Pre-computed daily
No infrastructure to maintain. No cron jobs, no indicator math, no data pipelines. TickerAPI handles computation and syncing.