“Why is it moving?”
Give users a structured answer that distinguishes observed price action, confirmed news, possible drivers, and uncertainty.
Stock market AI API
Turn market data into an answer.
Build stock research, comparison, sentiment, portfolio, and market-move features through one authenticated endpoint. Quan adds finance-specific reasoning and server-verified quote context where a raw data API stops.
- No card required
- Streaming or JSON
- Four public model aliases
market-brief.sh
curl https://stockup.cc/v1/query \
-H "x-api-key: $STOCKUP_API_KEY" \
-H "content-type: application/json" \
-d '{
"model": "quan-3.0",
"messages": [{
"role": "user",
"content": "Explain today’s TSLA move. Separate\nconfirmed facts from possible drivers."
}],
"stream": false
}'Use stream: true for Server-Sent Events.
Quote groundingServer-verified when supported
ComparisonsValuation through catalysts
Portfolio reviewExposure, overlap, priorities
Agent-readyOpenAPI + 8 MCP tools
Six useful building blocks
From ticker question to product feature.
Side-by-side research
Compare valuation, growth, profitability, margins, catalysts, risks, sentiment, and setup without separate prompts.
Narrative with caveats
Extract the current investor narrative, catalysts, counterarguments, and confidence instead of a context-free score.
Risk review
Surface concentration, factor overlap, drawdown exposure, key catalysts, and next research priorities.
Assumption-aware analysis
Explore dollar-cost averaging outcomes while making assumptions and limitations visible.
Connect price to evidence
Review SEC filings for earnings quality and risk, then relate those findings to the investment question.
Know the boundary
Reasoning layer, not an exchange feed.
StockUp is a strong fit when your user wants an explanation, comparison, research brief, or agent tool. Use a dedicated market-data vendor when you need bulk tick history, every asset class, exchange entitlements, or ultra-low-latency ticks.
- Use Quan for natural-language financial analysis and research workflows.
- Use server-verified quote context for supported current-stock questions.
- Use your primary data source for trading, compliance, and final validation.
| Need | Quan | Raw market API |
|---|---|---|
| Explain a move | Built for it | Glue code needed |
| Compare investment cases | Built for it | Not typical |
| Bulk OHLCV | Not the focus | Built for it |
| Agent tool use | MCP + OpenAPI | Varies |
Stock API FAQ
Before you integrate.
Can I use StockUp Quan as a Yahoo Finance API alternative?
Use Quan if the goal is grounded financial reasoning rather than raw endpoint parity. Read the detailed comparison for where it fits and where it does not.
Which model should I start with?
Start with Quan 3.4 L (quan-3.4-l) and its 100,000-token allowance. Use Quan 3.4 for flagship analysis and Deep Research for longer multi-stage workflows.
Can I call it from Python or TypeScript?
Yes. The API uses standard HTTPS and JSON, so any server-side language can call it. Keep your API key out of browser code.
Build the first version
Give one real market question to Quan.
Create a free key and see whether the answer is useful before committing a dollar.
Get my free key →