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"Information about F1 Racing" matching MCP servers:

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    This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.
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    MIT
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    Provides advanced Formula 1 analytics including real-time telemetry processing, tire degradation modeling, weather impact analysis, and Monte Carlo race strategy simulation for comprehensive F1 data analysis.
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    5
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    An MCP server for Meertrack that enables users to ask their AI agent about competitors' recent activities, digests, and product changes via natural language.
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    MIT
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    Provides AI assistants with access to University of Alabama at Birmingham's Research Computing documentation, enabling users to search and retrieve information about the Cheaha HPC cluster, SLURM job scheduling, storage systems, and available software tools.
    5
    MIT
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    Bridges Claude (or any MCP client) to manufacturing data via the i3X standard, enabling natural language queries about equipment status, hierarchy, and historical trends.
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    MIT
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    Provides programmatic access to CTFtime.org data for retrieving information about CTF competitions, team rankings, and event results. It enables users to search for upcoming events, analyze team performance, and access historical competition data through a standardized interface.
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    Connects NearIQ competitive intelligence to AI tools like Claude Desktop, Claude Code, Cursor, and Windsurf, enabling queries about competitors, reviews, rank tracking, and more.
    20
    MIT
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    Turns CREHQ's live location-intelligence REST API into native tools for AI agents, enabling natural-language queries about franchise brands, store locations, credit signals, and site tenancy history.
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    MIT
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    A minimal, token-efficient MCP server that combines stock prices and fundamentals with the macro and micro narrative around them — so an AI agent can reason about why a stock moved, what people are thinking about it, and what probable scenarios lie ahead.
    6
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    Enables natural-language queries about AI startup metrics like ARR and funding, with sourced, confidence-scored answers and contradiction detection.
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    MIT
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    Provides programmatic access to ClinicalTrials.gov API with 18 specialized tools for searching, analyzing, and retrieving detailed information about 400,000+ clinical trials worldwide, including filtering by condition, location, phase, sponsor, eligibility criteria, and outcomes.
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    MIT
  • F
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    A MCP server that wraps CISP enterprise information APIs into MCP tools, enabling AI agents to query business data like company profiles, trademarks, patents, and more.
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    MCP server that interfaces with the NCBI Entrez API to fetch detailed information about genes and proteins, enabling gene searches, gene/protein metadata retrieval, and symbol searching with organism filtering.
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    MIT
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    Provides a semantic concept layer over financial/economic data from multiple sources, enabling users to query data by concept and entity with automatic source selection and failover.
    MIT
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    Enables AI assistants to interact with the Open Targets Platform API to search and retrieve comprehensive data about target-disease associations, drugs, genes, and drug discovery information through GraphQL queries.
    37
    Apache 2.0