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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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    An AI Concierge replaces static forms with adaptive AI conversations that understand real situations, structure key information automatically, and trigger the right next step. Rigid forms cause drop-off, weaken qualification, and strip away context. Perspective uses adaptive AI to capture structured data and trigger automation, so you understand what truly matters to your customers and can make d
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    Enables AI-native statistical analysis and reproducible research workflows through MCP, including natural language planning, protocol-based analysis, Python/R cross-validation, and publication-ready figure generation.
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    Integrates with Orca AI's HUNT Platform API to search for information about people, companies, and entities, enabling AI assistants to access investigative intelligence and due diligence data.
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    Enables AI assistants like Claude to run backtests, fetch market data, list strategies, and analyze trading algorithms via natural language.
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    Provides access to curated AI news feeds and the ability to fetch and normalize any RSS/Atom/RDF feed, enabling AI agents to consume up-to-date content.
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    Local MCP server that ingests and normalizes recent AI, tech, and research news from multiple sources, exposing tools for media agents to query and retrieve article content on demand.
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    Provides access to the latest AI trends by querying Google News RSS and Hacker News API, enabling AI assistants to retrieve real-time trending topics.
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    Academic peer-review (HAKEM), research-gap finding, journal recommender (1,214 venues with predatory flags), duplicate publication checker, and article writer tools from Science AI Journal. Free local FTS5 tools + LLM-backed tools that bill the caller's account.
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