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Gathering Information from a Company's Website Root URL

  • Why this server?

    This server extracts structured data from unstructured web content, making it suitable for gathering information from a company's website.

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    A server that provides AgentQL's data extraction capabilities enabling AI agents to get structured data from unstructured web
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    183
    28
    JavaScript
    MIT License
    • Apple
    • Linux
  • Why this server?

    This server fetches web content in various formats (HTML, JSON, plain text, and Markdown), allowing you to retrieve the website's content for analysis.

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    Provides functionality to fetch and transform web content in various formats (HTML, JSON, plain text, and Markdown) through simple API calls.
    137,083
    TypeScript
  • Why this server?

    This comprehensive server can access web resources, among other things, potentially allowing access to information from a company's website.

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    A comprehensive Model Context Protocol server implementation that enables AI assistants to interact with file systems, databases, GitHub repositories, web resources, and system tools while maintaining security and control.
    16
    TypeScript
  • Why this server?

    If the target website is a wordpress website then this server is useful, as it can pull website information.

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    Links IoT devices to AI large models using the MCP and MQTT protocols, enabling natural language control, real-time AI responses, and complex instruction execution for interconnected IoT devices.
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    11
    Python
    MIT License
    • Apple
    • Linux
  • Why this server?

    This is useful for web scraping the target webpage for further information.

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    A Model Context Protocol (MCP) server implementation that integrates with FireCrawl for advanced web scraping capabilities.
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    8,264
    2,147
    JavaScript
    MIT License
    • Apple
    • Linux
  • Why this server?

    This server extracts and transforms web content into LLM-optimized Markdown, filtering out non-essential elements, which could be helpful for processing the information from a company's website.

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    Extracts and transforms webpage content into clean, LLM-optimized Markdown. Returns article title, main content, excerpt, byline and site name. Uses Mozilla's Readability algorithm to remove ads, navigation, footers and non-essential elements while preserving the core content structure.
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    4
    11
    MIT License
  • Why this server?

    Enables AI agents to control web browsers via a standardized interface for operations like launching, interacting with, and closing browsers. Useful for extracting infomration from the site in question

  • Why this server?

    Enables AI agents to interact with web browsers using natural language, featuring automated browsing, form filling, vision-based element detection, and structured JSON responses for systematic browser control.

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    Enables AI agents to interact with web browsers using natural language, featuring automated browsing, form filling, vision-based element detection, and structured JSON responses for systematic browser control.
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    23
    Python
    • Linux
    • Apple
  • Why this server?

    Enhances LLM applications with deep autonomous web research capabilities, delivering higher quality information than standard search tools by exploring and validating numerous trusted sources.

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    Enhances LLM applications with deep autonomous web research capabilities, delivering higher quality information than standard search tools by exploring and validating numerous trusted sources.
    65
    Python
    MIT License
    • Apple
  • Why this server?

    Although focused on stock market data, this server can fetch fundamental information about public companies, which may be present on their websites.

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    Provides real-time access to global stock market data including current prices, historical charts, and company financial information through a Model Context Protocol (MCP) server for AI assistants.
    TypeScript
    • Linux
    • Apple