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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 clients to analyze any company domain and determine its AI maturity tier (commercialized, deployed, declared, or none) with supporting evidence, via a single tool backed by an Apify actor.
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    An MCP server for searching and downloading books from Library Genesis, supporting EPUB, MOBI, PDF, and more through natural language queries.
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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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    Provides AI agents with real-time access to corporate credit data, including debt structures, bond pricing, and guarantor chains extracted from SEC filings. It enables complex financial analysis such as screening companies by leverage, tracing corporate hierarchies, and searching covenant language.
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    Apache 2.0
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    A headless, natural-language-driven automated modelling workflow for MIKE+, enabling users to inspect models, change parameters, run simulations, and analyze results without the MIKE+ GUI.
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    MIT
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    Enables natural language interaction with your T-Invest brokerage account for portfolio analysis, dividend tracking, and optional trading with safety confirmations.
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    Apache 2.0
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    Enables LLM clients to run GAUSS code against a real GAUSS installation, with persistent workspace state and full-precision data exchange.
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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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    MIT
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    Webhound is a research engine with an explicit effort control: a prompt defines the investigation and a dollar budget defines how much work it deserves. It returns cited reports or sourced datasets with the working documents, claims, sources, limitations, and evidence pack behind the answer.
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    A China A-share market data MCP server that enables AI agents to query factor data, market quotes, valuations, and run strategy backtests.
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    MIT