Market data for
Astro projects.
Use the TickerAPI Node.js SDK in Astro API endpoints and <code>.astro</code> components. Pre-computed financial data with no infrastructure to maintain.
Install the SDK.
Add tickerapi to your Astro project. Works with any rendering mode — static, server, or hybrid.
npm install tickerapi Set TICKERAPI_KEY in your .env file. Access it with import.meta.env.TICKERAPI_KEY.
Works in endpoints and components.
Call the SDK in API endpoints for JSON responses, or directly in .astro component frontmatter to render data at build time or on request.
import type { APIRoute } from "astro"; import { TickerAPI } from "tickerapi"; const client = new TickerAPI(import.meta.env.TICKERAPI_KEY); export const GET: APIRoute = async ({ params }) => { const summary = await client.summary(params.ticker!); return new Response(JSON.stringify(summary), { headers: { "Content-Type": "application/json" }, }); };
--- import { TickerAPI } from "tickerapi"; const client = new TickerAPI(import.meta.env.TICKERAPI_KEY); const summary = await client.summary("AAPL"); --- <div> <h2>AAPL</h2> <p>Trend: {summary.trend.direction}</p> <p>RSI: {summary.momentum.rsi_zone}</p> </div>
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 type { APIRoute } from "astro"; import { TickerAPI } from "tickerapi"; const client = new TickerAPI(import.meta.env.TICKERAPI_KEY); export const GET: APIRoute = async () => { const changes = await client.watchlist.changes(); return new Response(JSON.stringify(changes), { headers: { "Content-Type": "application/json" }, }); };
{ "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 type { APIRoute } from "astro"; import { TickerAPI } from "tickerapi"; import Anthropic from "@anthropic-ai/sdk"; const client = new TickerAPI(import.meta.env.TICKERAPI_KEY); const anthropic = new Anthropic(); export const GET: APIRoute = async ({ params }) => { const summary = await client.summary(params.ticker!); const msg = await anthropic.messages.create({ model: "claude-sonnet-4-20250514", max_tokens: 1024, messages: [{ role: "user", content: `Analyze this stock data:\n${JSON.stringify(summary)}`, }], }); return new Response(JSON.stringify({ analysis: msg.content[0].text }), { headers: { "Content-Type": "application/json" }, }); };
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.