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"How to connect with a Confluence page and retrieve its context" matching MCP servers:

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    Extracts people (names and titles) from a company's team, leadership, or about page given a domain. Uses Apify to crawl and return structured data, with optional filters for seniority and email inclusion.
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    MIT
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    提供A股实时行情、历史K线、财务报表、技术指标等全方位数据查询的MCP服务器,支持盘中即时更新及批量查询。
    24
    MIT
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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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    MIT
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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
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    Provides comprehensive A-share (Chinese stock market) data including stock information, historical prices, financial reports, macroeconomic indicators, technical analysis, and valuation metrics through the free Baostock data source.
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    MIT
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    MCP server adapter that exposes A-share stock data tools, prompts, and resources via FastMCP, enabling querying of stocks, K-lines, financials, sectors, and market hot spots through natural language.
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    Enables AI agents to perform corpus analysis tasks such as discovery, search, and data access via the Model Context Protocol.
    9
    MIT
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    Enables users to query Chinese A-share stock data, including stock basics, historical prices, financial reports, and macroeconomic indicators.
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    MIT
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    Enables searching, downloading, and exporting academic papers from 20+ scholarly sources including arXiv, PubMed, and Semantic Scholar. Supports multi-source concurrent search, citation network tracing, and export to CSV, RIS, and BibTeX.
    MIT
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    Exposes Vedic astrology tools for birth chart, dasha, transit calculations, and question context analysis.
    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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    Enables searching and discovering machine learning papers, state-of-the-art benchmarks, tasks, datasets, methods, and leaderboards from Papers with Code. Supports mapping papers to their benchmark results and browsing evaluation tables.