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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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    Enables AI agents to hire real human operators for tasks requiring physical presence, human perception, or judgment, such as verification, testing, data collection, and physical-world tasks.
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    MIT
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    Enables AI agents to recruit real humans for evaluation tasks like surveys, A/B tests, and ratings on text, images, audio, and video, returning aggregated results directly into the conversation.
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    Simulate hundreds of AI agents to predict how communities react to events and policies. Upload any document (PDF, Markdown, text) and DeepMiro spawns a diverse swarm of AI agents that debate, share, and form opinions — then delivers a calibrated prediction report. Free and open-source.
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    AGPL 3.0
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    MCP server providing 25 financial calculation tools in Spanish: ratios, DuPont, Altman Z-Score, Piotroski F-Score, WACC, CAPM, DCF, multiples, NPV/IRR, break-even, AR aging, depreciation, loan amortization, indirect cash flow, and Chilean tax helpers. Pure computation, no external connections.
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    MIT
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    MCP server for the Internet Archive's Wayback Machine. Search archived snapshots, extract page text from a specific date, track how a site has changed over time, check if broken links are recoverable, and perform research across Internet Archive collections.
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    Enables AI agents to perform corpus analysis tasks such as discovery, search, and data access via the Model Context Protocol.
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    MCP server providing 29 A-share analysis skills including real-time data, capital flow, limit-up tracking, technical/fundamental analysis, backtesting, risk control, and Xueqiu portfolio tracking, enabling AI agents to execute market research and strategy tasks.
    Apache 2.0