Market data inside
your Custom GPT.
Connect TickerAPI as a GPT Action. Your Custom GPT gets market summaries, technical scans, and comparisons — giving it real financial context for conversations.
Add as a GPT Action.
In the GPT Builder, go to Configure → Actions → Create new action. Paste the OpenAPI schema below. Add your API key under Authentication (API Key, Bearer token).
openapi: 3.1.0 info: title: TickerAPI version: "1.0" servers: - url: https://api.tickerapi.ai paths: /v1/summary/{ticker}: get: operationId: getSummary summary: Get a market summary for a ticker parameters: - name: ticker in: path required: true schema: type: string /v1/scan/oversold: get: operationId: scanOversold summary: Find oversold assets /v1/compare: get: operationId: compareAssets summary: Compare multiple tickers parameters: - name: tickers in: query required: true schema: type: string
This is a simplified schema. The full OpenAPI spec is available in the docs.
Multi-step analysis.
Your GPT can chain actions — scan for oversold stocks, get a full summary, then compare against peers. Each call returns categorical data the model understands without extra prompting.
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.
{ "ticker": "AAPL", "changes": [ { "field": "rsi_zone", "from": "neutral", "to": "oversold" }, { "field": "trend", "from": "uptrend", "to": "downtrend" } ] }
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 your agent 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.
Natural language access
Users ask your GPT questions like "What's oversold today?" — the GPT calls TickerAPI automatically and reasons about the categorical response.
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.