OptionsFlow MCP Server

OptionsFlow MCP Server – A Comprehensive Options Analytics Engine for AI Assistants

The OptionsFlow MCP server fills a critical gap for developers building AI‑powered trading tools: it turns raw market data from Yahoo Finance into actionable options insights without the need for custom parsing or proprietary APIs. By exposing a set of well‑structured tools, the server lets language models compute Greeks, implied volatility, and risk metrics for both individual options and common strategies such as credit spreads or covered calls. This eliminates the boilerplate that would otherwise be required to fetch, clean, and analyze options chains.

At its core, the server accepts a simple JSON payload describing a symbol, strategy type, and expiration date. It then retrieves the full options chain, filters by delta or width parameters, and calculates a suite of metrics. For spreads it reports credit received, maximum loss and profit, probability of profit, and risk‑reward ratio. For single‑leg strategies like cash‑secured puts or covered calls it provides premium, upside cap, and downside protection figures. All outputs include the relevant Greeks (net delta, theta, gamma) so that models can reason about time decay and sensitivity to price movements. The ability to return a unified, machine‑readable response makes it trivial for downstream workflows—such as portfolio construction or automated trading signals—to consume the data.

Key capabilities include:

• Full options chain processing with Yahoo Finance integration, ensuring up‑to‑date market data.
• Theoretical Greeks calculation using Black‑Scholes, giving models a quantitative foundation for risk assessment.
• Strategy‑specific risk metrics (credit, max loss, probability of profit) that are pre‑formatted for quick interpretation.
• Liquidity checks through bid‑ask spread, volume, and open interest validation to flag illiquid positions.
• Position sizing guidance based on maximum loss tolerances and probability thresholds.

Real‑world use cases span from a research assistant that generates daily options trade ideas, to an automated portfolio manager that schedules rebalancing based on risk‑reward thresholds. A Claude or GPT model can ask the server for “evaluate a 30‑day cash‑secured put on AAPL with delta 0.3” and receive a ready‑to‑use report, enabling rapid prototyping of strategies without hand‑coding financial formulas.

Integration is straightforward: the server registers itself in a Claude desktop configuration, and developers invoke the tool via the MCP interface. Because the response is already JSON‑structured, downstream systems can immediately parse and act on the data, whether that means updating a dashboard, triggering an order, or feeding into a larger decision‑making pipeline. OptionsFlow’s unique advantage lies in its end‑to‑end automation—from market data retrieval to risk assessment—allowing AI assistants to become truly intelligent trading partners.