Large language models are good at reasoning about numbers and bad at knowing them. Ask Claude which Polymarket wallets are actually profitable and you will get a confident answer assembled from training data that was already stale when the model shipped.
The Model Context Protocol fixes that by letting the model call your data directly. This post walks through a working example: a small MCP server that puts live Polymarket whale analytics into Claude Desktop, Cursor, or any other MCP client.
The server is open source and MIT licensed, so you can read the whole thing: github.com/orcalayer/orcalayer-mcp.
What MCP actually does
An MCP server exposes three kinds of capability to a model:
