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"Learning to Create an Expert Python Program to Exit GitHub" 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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    A specialized MCP server that provides institutional-grade financial data and market research via the Finnhub API. It enables AI agents to function as equity researchers, generating professional market reports and high-fidelity analysis for stock tickers.
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    Provides GitHub open-source intelligence via MCP tools for discovering trends, evaluating repository health, comparing projects, and analyzing users, issues, and releases. It includes a CLI and can be used with AI assistants like Claude or Cursor.
    MIT
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    An MCP server providing progressive discovery tools for SDMX statistical data, enabling AI agents to explore and access SDMX-compliant repositories through interactive tools, resources, and prompts.
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    MIT
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    Query iOS App Store revenue and download estimates for any app directly from your agent. Two tools: estimate_app returns monthly revenue and downloads with a confidence label (verified / calibrated / modeled), and search_apps resolves an app name to its App Store id.
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    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