About
A Python-based MCP server that fetches iRacing profile statistics, rating charts, and other data for custom applications. It integrates with MCP clients like VS Code and Claude Desktop.
Capabilities

Overview
iRacing MCP bridges the gap between the highly detailed racing simulation platform and modern AI assistants by exposing a rich set of data through the Model Context Protocol. It solves the problem of limited, manual access to iRacing statistics and telemetry for developers who want to build data‑driven tools, dashboards, or conversational agents. By encapsulating the iRacing API behind MCP, the server lets AI clients query race results, driver profiles, and performance charts without handling authentication or API pagination themselves.
The server’s core value lies in its simplicity and extensibility. Developers can spin it up with a single command, supply their legacy credentials, and immediately start issuing MCP calls. The current feature set includes retrieving a driver’s full profile statistics and generating an iRating chart for any category. These endpoints are already useful for building leaderboard widgets, performance analytics, or chat‑based race summaries. The design anticipates future expansion—new tools for telemetry, session data, or event scheduling can be added with minimal friction.
Key capabilities are presented in plain language through MCP resources and tools. A resource represents a data entity such as “profile” or “iRating chart,” while a tool is an executable action that can be invoked by an AI assistant. This separation allows the server to offer both read‑only data and dynamic computations, making it a versatile backend for both static dashboards and interactive conversational agents. The server also supports sampling controls, enabling developers to fine‑tune the amount of data returned and keep responses lightweight.
Real‑world use cases abound in racing analytics, fan engagement, and automated coaching. A sports broadcaster could query live iRating changes during a race to update commentary feeds. An esports team might use the server to feed performance metrics into an internal dashboard, while a hobbyist could build a chatbot that answers “Who has the highest iRating in Formula One?” questions on demand. Because MCP is designed to be client‑agnostic, the same server can power web apps, desktop assistants like Claude Desktop, or VS Code extensions without any client‑side code changes.
What sets iRacing MCP apart is its focus on developer ergonomics. By handling authentication, rate limiting, and data formatting internally, it removes common pain points when working with the iRacing API. The server’s open‑source nature invites community contributions, ensuring that new features—such as real‑time telemetry or advanced event filtering—can be added quickly. For developers looking to embed racing data into AI workflows, iRacing MCP provides a lightweight, standards‑compliant gateway that turns raw simulation data into actionable insights.
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