For Quant Traders

Skip the OPRA pipeline. Start with the answers.

15+ years of scored options data — REST, MCP, same dataset the agentic AI runs on.

Get started See the quant stack
100/min
API rate limit
MCP
For Cursor / Claude / ChatGPT
15+ y
Of historical chains
Same
Dataset as the AI stack
As featured in
NBC
ABC
CBS
AP
Benzinga
Digital Journal
Business Life
The New York Telegraph
Insider Weekly
Nation Today
International Business Journal
Tampa Bay Observer
Woman's Week
NBC
ABC
CBS
AP
Benzinga
Digital Journal
Business Life
The New York Telegraph
Insider Weekly
Nation Today
International Business Journal
Tampa Bay Observer
Woman's Week
A quant’s loop, on the platform

Research → backtest → ship. No ETL.

Idea → backtest → production. Same scored archive, three surfaces, no ETL.

Research: ask the data

REST API + MCP, same scored dataset

AGENT MODEL GET 200 { }
  • 80+ derived metrics, JSON over HTTPS, 100 req/min
  • MCP server for Cursor / Claude / ChatGPT
  • Same scored data the UI and agentic-AI stack use
Backtest: 15+ y of chains

Any multi-leg structure, any date range

AGENT MODEL 2010 SIM WINDOW NOW
  • Multi-leg structures, any expiry, any strike
  • Trade-by-trade ledger with realised P&L per setup
  • Same dataset as the agentic-AI training set — no drift
Production: alerts to your stack

Webhooks + JSON payloads = drop-in integration

AI agents and ML models triggering alerts across five delivery channels AGENT MODEL RULE score >= 90 Email SMS Slack Discord { } Webhook
  • Webhook payloads include the full scored event
  • Rate-controlled, retried, signed for verification
  • Same alert engine that powers every channel
Stop running an OPRA pipeline as a hobby. Free to test endpoints. Vega for production rate limits.
Get started
Why quants pick this

Most options vendors give you raw data and walk away.

Four things this gets right that a CSV-dump vendor does not.

REST over scored data

Chains, Greeks, 80+ derived metrics, signals, Smart Money, historical analytics. JSON, standard auth, 100 req/min.

MCP for AI assistants

Drop the server into Cursor, Claude, or ChatGPT and ask the agent options questions in plain English.

15+ years queryable. No ETL.

Daily chains, Greeks, and derived metrics — exposed over both the API and the workstation. One pipeline.

One dataset everywhere

API matches UI matches MCP matches alerts matches AI. Zero research-vs-prod drift.

Optionomics vs OPRA + ETL + analytics-as-a-service

A raw OPRA feed is not research infrastructure.

Buy ticks, stand up a DB, write the analytics. Or skip a six-month project and ship.

What you actually need
Optionomics
OPRA + DIY ETL + analytics
15+ years of full chain snapshots, queryable
Partial
REST API with scored / derived endpoints (UOA, signals, …)
MCP Server for AI assistants
Same dataset across UI, API, MCP, alerts
Partial
Strategy backtester on the same chain history
Partial
Cost
Skip the data engineering project. Start with the API. Free plan to test endpoints. Vega plan for production.
Get started
For every trading style

Pick the workflow built for how you trade

Day Traders
Live tape, UOA, AI Signals, and alerts before the screenshot drops.
Swing Traders
Trade Ideas, Smart Money, daily analytics, and multi-day positioning.
Options Writers
IV percentile, skew, term, max pain, builder, and Vega backtests.
Quant Traders
REST API, MCP, historical data, flow aggregates, and alert webhooks.
FAQ

Quant Traders — Frequently Asked Questions

Everything systematic traders ask before signing up.

Full chain snapshots, Greeks, 80+ derived metrics, Unusual Score, AI Signals, Smart Money flags, daily analytics, and the full historical archive.

With our MCP server configured in Cursor, Claude, or ChatGPT, you can ask the assistant questions about live options data, AI Signals, or historical chains and it queries the platform directly — no copy-paste, no stale context.

Yes — the strategy backtester is queryable both in the UI and via the API. Run any multi-leg structure across the full 15+ year archive, get back a trade-by-trade ledger with realised P&L per setup.

Yes — there is one canonical scored dataset. The UI, the API, the MCP server, the alert engine, and the agentic-AI pipeline all read from it. No drift between research, production, and what the AI is reasoning over.

Most systematic traders run on the Vega plan: API at production rate limits, MCP server, full historical archive, strategy backtester, and the agentic-AI stack.
Where to next

Explore the rest of the platform

API & Integrations

REST API, MCP server for AI assistants, and multi-channel alerts.

Learn more

Historical & Backtesting

15+ years of chains, time-travel, and a multi-leg backtester.

Learn more

AI Stack

Market commentary, trade ideas, signals, smart money, and earnings briefs.

Learn more

Pricing

Four monthly plans. Cancel anytime. Get started.

Learn more
Ready when you are

Skip the OPRA pipeline. Start with the API.

Free to test endpoints. Vega for production rates, the historical archive, the MCP server, and the backtester.

Get started See plans & pricing
Cancel anytime Month-to-month Vega plan unlocks production rate limits