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Deep Search MCP (Master Control Program)

  • Why this server?

    Provides unified access to multiple search engines and content processing services, enabling a 'deep search' across various platforms.

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    🔍 A Model Context Protocol (MCP) server providing unified access to multiple search engines (Tavily, Brave, Kagi), AI tools (Perplexity, FastGPT), and content processing services (Jina AI, Kagi). Combines search, AI responses, content processing, and enhancement features through a single interface.
    15
    54
    27
    TypeScript
    MIT License
    • Linux
  • Why this server?

    Enables sophisticated web searches through proxy servers using Tavily's API, allowing comprehensive web searches, question answering, and recent news retrieval.

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    quality
    Enables LLMs to perform sophisticated web searches through proxy servers using Tavily's API, supporting comprehensive web searches, direct question answering, and recent news article retrieval with AI-extracted content.
    1
    Python
  • Why this server?

    Enables advanced search and content extraction using the Tavily API, suitable for deep dives into specific topics.

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    A Model Context Protocol server enabling advanced search and content extraction using the Tavily API, with rich customization and integration options.
    4
    57
    1
    JavaScript
    MIT License
  • Why this server?

    A Model Context Protocol (MCP) server that enables semantic search and retrieval of documentation using a vector database (Qdrant).

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    A Model Context Protocol (MCP) server that enables semantic search and retrieval of documentation using a vector database (Qdrant). This server allows you to add documentation from URLs or local files and then search through them using natural language queries.
    14
    74
    JavaScript
    Apache 2.0
    • Apple
  • Why this server?

    A Python MCP server that enables semantic search through Search Labs blog posts indexed in Elasticsearch.

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    security
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    A Python MCP server that enables semantic search through Search Labs blog posts indexed in Elasticsearch, allowing Claude to intelligently retrieve relevant information from the blog content.
    Python
  • Why this server?

    Provides RAG capabilities for semantic document search using Qdrant vector database and Ollama/OpenAI embeddings, allowing users to add, search, list, and delete documentation with metadata support.

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    Provides RAG capabilities for semantic document search using Qdrant vector database and Ollama/OpenAI embeddings, allowing users to add, search, list, and delete documentation with metadata support.
    5
    4
    TypeScript
    Apache 2.0
  • Why this server?

    A Model Context Protocol (MCP) server that helps large language models index, search, and analyze code repositories with minimal setup

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    A Model Context Protocol (MCP) server that helps large language models index, search, and analyze code repositories with minimal setup
    4
    Python
    • Apple
    • Linux
  • Why this server?

    Provides deep git file-level forensics tools to analyze detailed file histories, changes, and patterns within git repositories, focusing on individual file analysis.

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    Provides deep git file-level forensics tools to analyze detailed file histories, changes, and patterns within git repositories, focusing on individual file analysis rather than repository-wide operations.
    4
    JavaScript
    Apache 2.0
    • Apple
  • Why this server?

    An MCP server implementation that integrates the Tavily Search API, providing optimized search capabilities for LLMs.

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    security
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    license
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    quality
    An MCP server implementation that integrates the Tavily Search API, providing optimized search capabilities for LLMs.
    1
    TypeScript
    MIT License
    • Apple