About Optionscanner
Free options calculators and the Optionscanner Learn library for any AI assistant. No account
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://optionscanner.ai/mcpclaude mcp add --transport http ai-optionscanner-optionscanner https://optionscanner.ai/mcp{"mcpServers":{"ai-optionscanner-optionscanner":{"type":"http","url":"https://optionscanner.ai/mcp"}}}Open in Cursor{"servers":{"ai-optionscanner-optionscanner":{"type":"http","url":"https://optionscanner.ai/mcp"}}}Open in VS Code{"mcpServers":{"ai-optionscanner-optionscanner":{"type":"http","url":"https://optionscanner.ai/mcp"}}}{"mcpServers":{"ai-optionscanner-optionscanner":{"serverUrl":"https://optionscanner.ai/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
10| Parameter | Type | Required | Description |
|---|---|---|---|
| days | number | Yes | Days to expiration. |
| legs | any | No | The legs of the trade, up to eight. Each has a side (buy or sell), a type (call, put or stock), a strike for options, a quantity, and optionally the price per share paid or received; a missing price is estimated from the implied volatility. |
| spot | number | Yes | Stock price in dollars. |
| iv_pct | number | Yes | Implied volatility, percent per year (30 means 30 percent). |
| rate_pct | number | No | Interest rate the model uses, percent per year. Default 4. |
| strategy | any | No | A standard structure built from the stock price: long_call, long_put, covered_call, cash_secured_put, bull_call_spread, bear_put_spread, bull_put_spread, bear_call_spread, iron_condor, long_straddle, long_strangle. Omit when passing legs. |
Details
The maintainer has not added details yet. Check the README in the repository.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.