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"A MCP server for integrating data requests with SharePoint" matching MCP servers:

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    Web Content Retrieval (full webpage, filtered content, or Markdown-converted), Custom User-Agent, Multi-HTTP Method Support (GET/POST/PUT/DELETE/PATCH), LLM-Controlled Request Headers, LLM-Accessible Response Headers, and more.
    3
    7
    MIT
  • A
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    MCP server for structured web data access, enabling local-market research and lead-list enrichment by returning business names, locations, ratings, and review signals from concrete queries.
    1
    MIT
  • A
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    An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.
    2
    27,145
    MIT
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    Real-time Korean web data for AI assistants — Naver Place reviews, Melon charts, Daangn/Bunjang marketplace, Naver News, Musinsa fashion rankings. 7 tools powered by Apify actors.
    7
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    MIT
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    Enables AI assistants to fetch, search, and organize menu information from For Five Coffee café. Provides access to complete menu data, category filtering, and item search capabilities through both MCP and REST API interfaces.
    4
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    Automatically crawls documentation websites, converts them to organized markdown files, and generates condensed cheat sheets. Intelligently categorizes content into tools/APIs and provides local-first access to downloaded documentation.
    3
    GPL 3.0
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    MCP server for AI agents -- fetch any URL with full JavaScript rendering (Playwright/Chromium) and convert to clean, token-efficient markdown. Works on React, Vue, Angular, and any JS-heavy page. Includes web search, batch fetching, binary file download, LRU cache, SSRF protection, and structured output.
    13
    MIT
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    An MCP server that lets AI assistants like Claude read LinkedIn data through your own logged-in browser session. Access profiles and companies, search for jobs, or get job details.
    17
    Apache 2.0