iRacing Data MCP Server

The iRacing Data MCP Server turns the rich, real‑time racing telemetry and profile data from iRacing into a first‑class resource for AI assistants. By exposing the simulation’s REST API through the Model Context Protocol, developers can ask an assistant to fetch a driver’s season recap, retrieve team statistics, or look up a member’s licensing details—all without leaving the conversational interface. This solves the common pain point of “manual API plumbing”: instead of writing custom wrappers or dealing with authentication flows, an assistant can call a simple, type‑safe tool that returns structured JSON.

At its core, the server provides a collection of tools such as , , , and . Each tool is annotated with Zod schemas, ensuring that the data returned to the assistant is validated and consistent. The automatic authentication layer manages cookie jars, session tokens, and optional API keys, so developers need only supply credentials once. Once authenticated, the assistant can request live data: a driver’s current season performance, historical career statistics, or even full team rosters. This immediacy is invaluable for applications that require up‑to‑date racing insights, such as dynamic race summaries or personalized driver analytics.

Developers benefit from the server’s dual interface. The MCP mode plugs directly into Claude, ChatGPT, or any LLM that supports Model Context Protocol, allowing conversational agents to perform data‑driven queries on demand. The CLI mode provides a quick way to script or automate data pulls, making it suitable for batch reporting or integration into CI pipelines. The combination of real‑time data access, type safety, and straightforward configuration means that both rapid prototyping and production deployments can leverage iRacing’s data without reinventing authentication or parsing logic.

Real‑world scenarios that shine with this server include:

• Race commentators: An AI can generate instant commentary or statistical insights during a live event.
• Team analytics dashboards: A bot can pull the latest season recaps and career metrics to feed into internal dashboards.
• Gaming communities: Discord bots or web apps can answer questions like “Who won the most races last season?” using a single tool call.
• E‑sports training: Coaches can query driver progress over time and share structured reports with trainees.

By integrating seamlessly into existing AI workflows, the iRacing Data MCP Server turns raw simulation data into conversational knowledge, giving developers a powerful, low‑maintenance channel to enrich their applications with real‑world racing intelligence.