iRacing Data MCP Server
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Alternatives to iRacing Data MCP Server
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- AlicenseNot gradedqualityDmaintenanceEnables AI-powered racing coaching and telemetry analysis for iRacing, providing real-time racing advice, car spotting, lap analysis, and conversational interaction with racing data through live telemetry streaming.2MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to query real-time and historical Formula 1 data through the OpenF1 API, providing tools for driver info, lap times, telemetry, race events, and more.MIT
- AlicenseAqualityDmaintenanceIntegrates iRacing with the Model Context Protocol to retrieve profile statistics and iRating charts for any category.29MIT

mcp-f1official
AlicenseNot gradedqualityCmaintenanceProvides Formula 1 data via the Ergast API, enabling users to check current standings, get race results, view the season schedule, and look up driver profiles.1 npmMIT- FlicenseNot gradedqualityCmaintenanceProvides live Formula 1 data such as driver standings, race results, and schedule for the current season, enabling users to ask about F1 without stale training data.1-
- FlicenseNot gradedqualityDmaintenanceEnables access to Formula 1 data from the openF1.org API, including driver information, race results, lap times, telemetry, pit stops, weather conditions, and live position data across multiple seasons.-
TDQS
Scored across 6 tools
The tools are mostly distinct in purpose (e.g., driver_lookup vs. get_team vs. login), but there is some overlap between get_member_career, get_member_recap, and get_members_profile, which all seem to retrieve member-related data with unclear boundaries. Without descriptions, it's ambiguous whether these tools serve different aspects of member information or could be consolidated.
The naming follows a consistent snake_case pattern throughout, with a mix of verb_noun (e.g., driver_lookup, get_member_career) and noun-only (e.g., login) styles. While not perfectly uniform in verb usage, the structure is readable and predictable, with only minor deviations from a strict convention.
With 6 tools, the count is reasonable for a data server focused on iRacing, covering key operations like login, member data retrieval, and team info. It's slightly lean but not overly sparse, as it includes essential functions without obvious bloat, though more tools might be expected for a comprehensive racing data service.
The tool set is significantly incomplete for an iRacing data server, lacking obvious gaps such as tools for race results, standings, schedules, or car/track data. It focuses narrowly on member and team profiles without covering broader racing data, which will likely cause agent failures when trying to perform common tasks like fetching race outcomes or event details.