Get stock quotes in Python
Build a Python quote request with environment credentials, timeout handling, nested response validation and UTC timestamps before storing market data.
Read the guide Developer field notes
Build with data.
Understand the details.
From your first quote to a recovering stream. Practical guides for the decisions that shape a market data integration.
Looking for request parameters? Browse the API reference for quotes, candles, screeners, discovery, research data and connection credentials.
01 / Integration guides
Quotes
Request market data with Node.js fetch
Use native Node.js fetch for server-side market quotes, distinguish HTTP and API failures, and return a small validated response to your frontend.
Read the guideBuild a watchlist with the batch quote API
Split a watchlist into batches of ten, preserve per-symbol failures and degraded results, and update quote rows without overwriting good data with zero.
Read the guideUnderstand quote timestamps and data freshness
Separate market time from receive time, handle missing prices and closed sessions, and define a visible freshness policy for a market data application.
Read the guide02 / Integration guides
Historical data
Export historical OHLCV to CSV with Python
Fetch standard candles, map max and min to high and low, sort and deduplicate timestamps, and export a reproducible CSV with a separate request manifest.
Read the guideChoose historical candle windows and adjustments
Understand candle counts, Unix-second from and to parameters, split and dividend adjustments, and checks for incomplete historical windows.
Read the guide03 / Integration guides
Streaming
REST vs WebSocket vs SSE for market data
Choose a market data transport by interaction pattern, recovery requirements and credential handling, with examples for reports, watchlists and dashboards.
Read the guideSubscribe to market quotes over WebSocket
Generate a streaming credential, send subscribe_quote, distinguish acknowledgements from quote updates, and plan reconnects without assuming event replay.
Read the guideReceive market data with Server-Sent Events
Inspect an SSE market data stream with cURL, connect a browser using a short-lived token, and handle named events, expired credentials and cleanup.
Read the guide04 / Integration guides
AI integrations
Ground an AI agent with market data through MCP
Design an MCP quote and candle workflow that resolves instruments, checks tool success and timestamps, and separates retrieved data from model interpretation.
Read the guidePut a guide into practice.
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