Open source options data MCP GitHub searches usually start the same way: you are wiring an AI assistant into the options market, you want live chains, Greeks, and put-call flow, and you would rather clone a repository than build the plumbing yourself. That is a reasonable instinct. GitHub hosts a growing set of Model Context Protocol servers that expose market data to assistants like Claude, and reading one is the fastest way to understand how the protocol works.
This guide does two things. First, it explains what an options-data MCP server actually is and what to look for when you evaluate an open-source one on GitHub. Second, it lays out where the free-and-open path quietly costs you, and how a licensed options-data MCP keeps the number your AI cites and the number in your spreadsheet in agreement. Every MarketXLS formula shown here was verified against the function library before publishing, and a free Excel template that uses them is available to download below.
Open source options data MCP GitHub: at a glance
| Consideration | Typical open-source GitHub MCP | Licensed options-data MCP (MarketXLS) |
|---|---|---|
| Data source | Often an unofficial or free public endpoint | Enterprise, licensed market data (QuoteMedia) |
| Redistribution rights | Frequently unclear for commercial use | Licensed for the product and its MCP surface |
| Freshness | May be delayed or cached, rarely flagged | Streaming and intraday, with a last-trade timestamp |
| Option chain | Basic pull, depth varies by repo | Full and active-contract chains |
| Greeks | Sometimes local, may be stale or absent | Delta, Gamma, Theta, Vega from the live price |
| IV and put-call flow | Often missing | 30-day IV, IV rank, put-call ratios built in |
| Excel parity | None, the MCP feeds the AI only | Same functions fill cells and answer prompts |
| Maintenance | Community, best-effort | Vendor-maintained with a support path |
The point of the table is not that open source is bad. For prototyping, learning the protocol, or a hobby project, a GitHub MCP is often exactly right. The point is that when you move toward real research or an advisor workflow, three things start to matter a great deal: where the data legally comes from, how fresh it is, and whether the same numbers reach both your AI and your spreadsheet. A licensed options-data MCP is built around those three concerns.
What an options-data MCP server actually does
Three ideas are bundled into the keyword, and separating them makes the rest of this easier.
MCP stands for Model Context Protocol, an open standard that lets an AI assistant call external tools and data sources in a structured way. Instead of pasting numbers into a chat by hand, the assistant asks a server for what it needs and gets back structured data it can reason about.
Options data means the full options surface: the chain of strikes and expirations, the Greeks (Delta, Gamma, Theta, Vega), implied volatility, options volume, and open interest. An options-data MCP turns those into callable tools rather than a web page you read by eye.
GitHub is simply where much of the open-source community publishes these servers. A repository gives you the code, an issues tab, and a license file. Reading one is genuinely useful, because it shows you the shape of the tools an assistant expects and how requests and responses are structured.
Put the three together and an options-data MCP server is a small program that answers an assistant's request for an option chain or a Greek with real data. The interesting differences between one server and the next are almost never about the protocol. They are about the data behind it.
How to evaluate an open-source options-data MCP on GitHub
If you are browsing GitHub for an options-data MCP, a short checklist will save you time later.
Read the license and the data terms first. The repository's own license (MIT, Apache, and so on) governs the code, but the data the server pulls has separate terms set by whoever provides it. A permissive code license does not grant you rights to redistribute the underlying market data. This is the single most common surprise for teams that ship something built on a free endpoint.
Check where the data comes from. Look for the exact source in the README or the request code. Free or unofficial endpoints can change, rate-limit, or disappear without notice, and they rarely carry any commercial-use guarantee. This guide does not endorse pulling from any site that prohibits it; the safe path is an official, licensed provider.
Ask whether it exposes freshness. Real-time is meaningless without a way to measure it. A well-built server tells you when a quote last printed. Many lightweight ones return a number with no timestamp, so you cannot tell whether it is two seconds or twenty minutes old.
Confirm Greeks and analytics are present and live. Some servers hand back a chain but no Greeks, or Greeks computed once and cached. For anything involving position sizing, you want Delta, Gamma, Theta, and Vega derived from the current option price.
Look at maintenance. Check the commit history, open issues, and whether someone answers them. A server you depend on is only as reliable as the person keeping it alive.
None of these are reasons to avoid open source. They are the questions that tell you whether a given repository fits a weekend experiment or a workflow other people will rely on.
Where the free-and-open path quietly costs you
An open-source options-data MCP has two subtle failure modes that show up only after you have built something on it.
The first is licensing. If the server reads from a source whose terms forbid redistribution, then the moment you expose that data through your own product or share it with clients, you may be offside. The code was free; the data was not. This is not a hypothetical for anyone building a commercial tool.
The second is consistency. Suppose your AI assistant pulls option data from one open-source MCP and your spreadsheet pulls from a different feed. The two can compute Greeks with different inputs, different risk-free rates, or different snapshot times. You end up reconciling numbers instead of using them. Ask the assistant for "the at-the-money call delta on SPY right now" and it may answer from a fifteen-minute-old quote with no flag that it is stale, while your sheet shows something else entirely.
A licensed options-data MCP addresses both at once. The data comes from a source you are permitted to use, and the same licensed functions feed your AI and your spreadsheet, so the two agree because they are the same calculation.
How MarketXLS exposes a licensed options-data MCP
MarketXLS has spent years building Excel functions on top of enterprise-grade, licensed market data. Those same functions are what the MarketXLS MCP server hands to an AI assistant. Here are the verified building blocks, grouped by job.
Underlying quotes and volatility context
Before you touch a single contract, you want the underlying price and a read on whether its options are cheap or rich:
=QM_Last("SPY") ' Most recent consolidated last price
=ImpliedVolatility30d("SPY") ' 30-day implied volatility
=ImpliedVolatilityRank1y("SPY") ' 1-year IV rank (0 to 100)
=Beta("SPY") ' Beta versus the broad market
ImpliedVolatilityRank1y is the quiet workhorse. It returns where current IV sits within its own one-year range, from 0 at the yearly low to 100 at the yearly high, so you can see at a glance whether the market is pricing options expensively.
Building an option contract symbol
Most contract-level functions need a properly formatted option symbol. OptionSymbol assembles it for you from the underlying, expiry, type, and strike:
=OptionSymbol("SPY", DATE(2026,8,21), "Call", 620)
' Returns the QuoteMedia symbol for that exact contract
You then nest that result inside the contract functions rather than typing a cryptic option symbol by hand.
Live contract prices and Greeks
With the symbol in hand, you can pull the contract's market data and compute its Greeks from the current price:
=Bid(OptionSymbol("SPY", DATE(2026,8,21), "Call", 620))
=Ask(OptionSymbol("SPY", DATE(2026,8,21), "Call", 620))
=QM_Last(OptionSymbol("SPY", DATE(2026,8,21), "Call", 620))
=QM_OpenInterest(OptionSymbol("SPY", DATE(2026,8,21), "Call", 620))
=opt_Delta(QM_Last("SPY"), QM_Last(OptionSymbol("SPY", DATE(2026,8,21), "Call", 620)), DATE(2026,8,21), "Call", 620)
=opt_Gamma(QM_Last("SPY"), 6.10, DATE(2026,8,21), "Call", 620)
=opt_Theta(QM_Last("SPY"), 6.10, DATE(2026,8,21), "Call", 620)
=opt_Vega(QM_Last("SPY"), 6.10, DATE(2026,8,21), "Call", 620)
=opt_ImpliedVolatility(QM_Last("SPY"), 6.10, DATE(2026,8,21), "Call", 620)
The opt_ family follows one consistent argument order: current stock price, market option price, expiry date, option type, and strike, with an optional risk-free rate and implied volatility at the end. Because Delta, Gamma, Theta, and Vega all take the live option price as an input, they refresh as the market moves rather than sitting frozen at a stale value.
The whole chain, plus volume and sentiment
When you want the surface rather than a single contract, and the flow context around it:
=QM_GetOptionChainActive("SPY") ' Most actively traded contracts
=QM_GetOptionChain("SPY") ' Full option chain
=opt_TotalVolumeOptions("SPY") ' Total daily options volume
=opt_TotalOpenInterestOptions("SPY") ' Total options open interest
=opt_PutCallVolRatio("SPY") ' Put-call volume ratio
=opt_PutCallOIRatio("SPY") ' Put-call open-interest ratio
A put-call volume ratio above 1.0 means more puts than calls are trading, often hedging or defensive flow; below 1.0 leans bullish. Pair it with IV rank to judge whether that positioning is cheap or expensive. These are context indicators, not trade signals.
The approach: one source, two surfaces
Here is the educational hypothesis behind a licensed options-data MCP. If the number your AI cites and the number in your spreadsheet come from the same licensed function, calculated the same way, then you can move between a chat window and Excel without reconciling anything. You ask Claude, "what is the Delta on the SPY August 620 call, and how does it change if the index drops two percent," and the assistant calls the same opt_Delta primitive that fills your workbook. The answer it gives and the cell you are looking at agree, because they are the same calculation.
That consistency is not a luxury when the underlying is moving. It is the difference between acting on a current, defensible number and acting on a stale one. None of this is a recommendation to trade any particular contract. It is a way to make sure the data you reason from is fresh, licensed, and consistent, whatever you decide to do with it.
The template: an options-data workbook you can download
The free Excel workbook that accompanies this guide is built entirely on the verified functions above. It ships in two versions. The sample is pre-filled with a static snapshot so you can explore the layout immediately. The template version uses live MarketXLS formulas, so every cell refreshes when you open it with MarketXLS installed.
Both versions share seven sheets:
- Cover lays out the workbook and a table of contents.
- How To Use is a step-by-step tutorial and an input legend.
- Inputs holds the yellow cells you edit: focus ticker, expiry, days to expiration, risk-free rate, an IV-rank filter, and a watchlist. These flow into the other sheets.
- Options Data Dashboard is the screener. KPI tiles report median IV30, median IV rank, names passing your filter, total options volume, the median put-call ratio, and the VIX level. The table lists each watchlist name with price, IV, IV rank, volume, open interest, put-call ratios, expected move, and beta.
- Live Option Chain builds an at-the-money ladder for your focus ticker: call bid/ask/last, IV, and the full Greek set on the left, the matching puts on the right, with open interest per strike.
- Open Source vs Licensed is a neutral side-by-side of the trade-offs discussed here, from data source and redistribution rights through freshness, Greeks, and Excel parity.
- Methodology & Glossary documents the data sources, the MCP connection, the calculations, and the assumptions.
Every sheet carries a "MarketXLS Functions Used in This Sheet" box, so you always know which formula to copy into your own model.
Download the templates:
- - Pre-filled with current data
- - Live-updating formulas
Reading the Open Source vs Licensed sheet
The comparison sheet exists so you can make the trade-off deliberately rather than by default. Each row is a dimension that tends to matter more as a project grows up: the data source and whether you are allowed to redistribute it, how fresh the quotes are and whether that freshness is exposed, whether Greeks and put-call analytics are present and live, and whether the same numbers reach both your AI and your spreadsheet.
Open source wins on cost and transparency and is a fine place to learn. A licensed MCP wins on data rights, freshness, and consistency across surfaces. Neither answer is universal. The sheet just makes the choice visible so it is not something you discover after you have shipped.
Connecting the workbook to your AI assistant
The workbook stands on its own in Excel, but the reason it is framed around MCP is that the same functions answer AI prompts. Once the MarketXLS MCP server is connected to your assistant, a prompt like "pull the active option chain for SPY with Greeks and flag anything with a put-call ratio above 1.2" routes to QM_GetOptionChainActive, opt_Delta, and opt_PutCallVolRatio. The numbers the assistant returns are the numbers in your sheet, because they are the same primitives.
For more on the connector itself, see our companion pieces on a real-time options API over MCP and the broader options market data over MCP walkthrough. To see how the Greeks and analytics work inside a spreadsheet, read options data in Excel, and browse the full MarketXLS features page for the complete function catalog.
FAQ
What is an open source options data MCP on GitHub?
It is a Model Context Protocol server, published in a public GitHub repository, that exposes options market data (chains, Greeks, implied volatility, volume, and open interest) to an AI assistant. The code is open, which makes it a good way to learn the protocol. The data behind it, and the license that governs that data, is a separate question you have to check per repository.
Is open source data free to use commercially?
Not necessarily. The repository's code license and the terms of the underlying data are two different things. A permissive code license does not grant you rights to redistribute market data pulled from a third-party source. If you plan to ship a product or share data with clients, confirm the data terms allow it, or use a licensed provider.
How is a licensed options-data MCP different?
A licensed MCP sources its data from an enterprise provider under a contract that permits its use, exposes freshness so you know how current each quote is, and, in the MarketXLS case, uses the same functions in Excel and in the AI connector. That last detail keeps a chat answer and a spreadsheet cell from disagreeing.
Which Greeks can I calculate, and are they live?
Delta, Gamma, Theta, and Vega are available through opt_Delta, opt_Gamma, opt_Theta, and opt_Vega, along with implied volatility via opt_ImpliedVolatility. Because each one takes the current option price as an input, the Greeks update as the market moves rather than sitting frozen.
How do I pull a whole option chain instead of one contract?
Use QM_GetOptionChainActive for the most actively traded contracts or QM_GetOptionChain for the full chain. For a single contract, build the symbol with OptionSymbol and pass it to Bid, Ask, QM_Last, or QM_OpenInterest.
Do I need to write code to use the MarketXLS MCP?
No. The Excel side is just formulas, and the MCP side is a connector you point your AI assistant at. You ask questions in natural language and the assistant calls the functions. There is no manual data export involved; the data flows through licensed market-data functions.
The bottom line
Open source options data MCP GitHub projects are a genuinely good way to learn the protocol and to prototype quickly. Where they get you into trouble is not code quality; it is data licensing, freshness, and the drift that appears when your AI and your spreadsheet pull from different feeds. A licensed options-data MCP removes that class of problems by exposing live chains, Greeks, IV, and put-call analytics from one source that serves both Excel and your AI assistant, so the chat window and the workbook stay on the same tick.
Download the template above, open it with MarketXLS, and start with the focus ticker and the Live Option Chain sheet. When you are ready to connect the same primitives to your AI assistant, explore the full platform at marketxls.com or book a demo to see the MCP connector in action. For plan details, see MarketXLS pricing.
Educational use only. Nothing here is investment advice or a recommendation to buy or sell any security or contract. Options trading involves substantial risk of loss.
