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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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    2
    MIT
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    A Python implementation of the Model Context Protocol (MCP) server that enables searching and extracting information from arXiv papers, designed to be extensible with additional MCP tools.
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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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    Enables time series analysis following Box-Jenkins-Treadway methodology, supporting guided or autonomous modes for model identification, estimation, and diagnosis via an LLM.
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    GPL 2.0
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    An MCP server for the NASA Astrophysics Data System (ADS) that enables searching, citation graph traversal, and bibliography management for astrophysics literature. It provides tools for computing citation metrics, resolving astronomical object names, and managing paper libraries through natural language.
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    MIT
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    A safety-bounded MCP server for discovering data-acquisition devices and performing finite analog-voltage and digital-input reads through NI's nidaqmx Python package.
    9
    Apache 2.0
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    Local MCP adapter for public Stock Trends API resources, enabling credential-free access to public resources and a workflow cost estimation tool. It does not generate investment advice; it only translates published API responses for MCP clients.
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    MIT
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    A Python MCP server providing 11 tools for querying KenPom basketball analytics, including efficiency ratings, game predictions, four factors, and more through Claude.
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    Enables AI assistants to work with Taranis NG OSINT platform through a typed, safety-oriented interface over its REST API, covering collection, analysis, reporting, and administration workflows.
    European Union Public 1.2
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    Exposes tools and resources for human-supervised geological modelling from borehole data, including validation, 3D implicit model construction with GemPy, and uncertainty analysis, with a deterministic audit trail.
    MIT
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    A virtual statistician MCP server that provides real statistical methods—design of experiments, hypothesis testing, regression, SPC, MSA—via tested Python libraries, with plain-language interpretations and plotted outputs.
    MIT
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    PyPSA MCP is a Model Context Protocol (MCP) server for creating, analyzing, and optimizing energy system models using PyPSA (Python for Power System Analysis).
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    MIT
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    Enables LLMs and MCP clients to execute Python and C++ code using ROOT's PyROOT interface, with support for graphics and error detection.
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    BSD 2-Clause "Simplified"