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"A powerful MCP server for web search and information gathering" matching MCP servers:

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    MCP server that parses web pages into clean markdown via Crawl4AI's HTTP API, exposing parse_page and health-check tools with configurable proxy and timeout.
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    MIT
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    An MCP implementation that integrates the Brave Search API, providing comprehensive search capabilities including web, local business, image, video, news searches, and AI-powered summarization.
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    MIT
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    Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.
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    Inno Setup
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    Enables AI assistants to perform real-time web searches and retrieve AI-generated answers using the Yandex Search API. It provides tools for accessing up-to-date internet information with support for both raw search results and summarized content via the Yazeka model.
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    Enables web search and AI-summarized answers via an x402-gated gateway, with options for structured results or enriched summaries, accessible as an MCP server.
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    Enables Web3-focused web searches via the OptimAI External Search API, providing tools to start, retrieve, list, and cancel searches from any MCP-compatible AI host.
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    ISC
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    Enables MCP clients to perform intelligent web searches via Traylinx's Agentic Search API, returning text summaries and structured data like HTML, images, and news.
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    MIT
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    Enables web search for AI agents with pay-per-search in USDC, no API keys needed.
    MIT
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    Enables web search and deep multi-source research for Cerase agents via LiteLLM proxy, with billing attribution per agent.
    MIT
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    MCP-first A/B testing server that enables agents to manage experiments (create, update traffic splits, read results, apply winning variants) from tools like Claude Code, with self-hosted Cloudflare backend.
    MIT
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    Enables AI agents to search through Memex conversation history and local project files to retrieve specific commands, code snippets, and technology overviews. It utilizes smart context management and faceted filtering to provide relevant search results without causing context overload.