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105,186 servers. Updated
20 Best GitHub MCP Servers: compared and ranked, October 2026Ranked from 1,950 matching servers on stars, growth, downloads and maintenance. Updated .

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"Methods to Scrape a Website and Fetch Markdown Files from GitHub" matching MCP servers:

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    Enables AI agents to fetch one or many web pages concurrently and receive clean, LLM-ready Markdown with navigation, ads and boilerplate stripped away, plus extracted metadata such as title, description, author, Open Graph tags and canonical URL. It runs locally over stdio with no API key or account, requiring only a single command.
    3
    MIT
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    Fetches a URL and returns the main content as clean Markdown, using plain HTTP when possible and headless Chromium for JavaScript-rendered or bot-protected pages.
    1
    28 PyPI
    MIT
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    Enables structured extraction of methods and reproducibility heuristics from academic papers, allowing AI agents to obtain metadata, full text, structured methods, code repository discovery, and a no-clone reproducibility verdict from a paper URL.
    8
    MIT
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    Enables AI models to fetch real web pages while automatically bypassing anti-bot protections, login walls, and JS rendering, then returns clean, token-efficient article content.
    4
    MIT
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    Recommends study designs for a research question, states the identifying assumptions to verify, and returns runnable R, Python, or Julia code with a formatted citation for every source, drawn from methodological textbooks, an R package, and research articles on causal inference, econometrics, statistics, and machine learning.
    6
    MIT
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    Fetch URLs and return clean, LLM-ready markdown with metadata and layered prompt injection defense. Configurable timeouts, word limits, JS rendering, and link extraction. All-in-one MCP server + CLI.
    1
    1
    MIT
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    Generates test files locally (images, PDFs, CSVs, corrupted files, etc.) from natural language prompts, with configurable sizes and safety limits.
    10
    MIT
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    Enables agents to run Google searches across web, images, videos, news, books, shopping, scholar, patents, and AI Mode without an API key, using a cookie-bootstrapped HTTP fast path with a headless browser fallback, proxy rotation, and adaptive cooldowns. Every response reports an explicit status (ok, blocked, rate_limited, empty, error) so results are never fabricated.
    2
    22
    MIT
  • F
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    A lightweight MCP server for basic file operations, enabling reading, writing, and listing files securely via the Model Context Protocol.
    3
    1
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    A comprehensive web scraping server that transforms web content into clean, agent-ready Markdown with automatic citations and efficient caching. It features a robust suite of tools for metadata extraction, sentiment analysis, SEO auditing, and security scanning while strictly adhering to robots.txt policies.
    48
    11 npm
    48
    MIT
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    A web-fetch MCP server for LLM agents that fetches pages with an escalation ladder through different engines, raising FetchBlocked instead of returning blocked content.
    2
    2
    Apache 2.0
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    Model Context Protocol server for fetching web content and processing images. This allows Claude Desktop (or any MCP client) to fetch web content and handle images appropriately.
    1
    715 npm
    41
    MIT
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    MCP server for web page fetching (converting to Markdown/text with automatic fallback between Tavily and Firecrawl) and web search via Tavily.
    2
    MIT
  • A
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    A generic Markdown vault MCP server with FTS5 full-text search, semantic vector search, frontmatter-aware indexing, incremental reindexing, and non-markdown attachment support that exposes search, read, write, and edit tools.
    44
    325 PyPI
    34
    MIT
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    A Model Context Protocol (MCP) server that provides a local-first RAG engine for your markdown documents. It uses a file-based Milvus vector database to index your notes, enabling LLMs to perform semantic search and retrieve relevant content from your local files.
    3
    64
    Apache 2.0
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    Reduces token consumption by 73-87% by cleaning web and API data before it reaches the LLM context window. Supports fetching URLs, searching the web, optimizing JSON, and more.
    6
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