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"A semantic web search for 'Exa'" matching MCP servers:

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    Enables AI assistants to perform real-time web searches, company research, content crawling, LinkedIn searches, and deep research using the Exa AI Search API. Provides comprehensive web information retrieval capabilities in a safe and controlled manner.
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    13,273
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    MIT
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    A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
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    Exposes the Exa web search API as an MCP server, providing tools for web searching, content retrieval, and similar page discovery. It also supports advanced features like AI-generated answers and automated research task management.
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    An MCP server that enables AI models to perform Google Web searches using the Gemini API, complete with citations and grounding metadata for accurate information retrieval. It is compatible with Claude Desktop and other MCP clients for real-time web access.
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    Apache 2.0
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    Enables AI agents to perform semantic search over codebases by converting natural language queries into efficient search patterns like grep and ripgrep. It utilizes LLMs to verify relevance and find code snippets that traditional keyword-based searches might miss.
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    Enables free web searching using Google search results without the need for API keys or authentication. It returns structured data including titles, URLs, and descriptions with configurable result limits.
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    MIT
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    Enables comprehensive web searching and content extraction using multiple search engines (Bing, Brave, DuckDuckGo) without API keys. Provides tools for full web searches with content extraction, quick search summaries, and single webpage content retrieval.
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    MIT
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    Enables semantic search over markdown files to find related notes by meaning rather than keywords, and automatically detect duplicate content before creating new notes.
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    BSD 2-Clause "Simplified"
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    Local offline semantic search over documents (txt, md, pdf, docx, pptx, csv). Indexes folders into a LanceDB vector database with multilingual embeddings and supports hybrid vector + keyword search via Reciprocal Rank Fusion. No API keys, no cloud, no Docker required.
    Last updated
    26
    AGPL 3.0