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    A Model Context Protocol server that provides accurate Chinese Ziwei Doushu astrology chart calculations and horoscope analysis, enabling AI assistants to generate personalized astrological readings through natural language queries.
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    MIT
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    Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.
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    MIT
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    Model Context Protocol server exposing the SCOUTS-AI web search API as a single web_search tool for AI agents. No API key required.
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    Discover which MCP servers can interact with real-world entities like restaurants, hotels, and salons by querying the Dock AI registry using domain names.
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    Enables AI agents to check whether a public website is crawlable, understandable, and ready for AI search workflows through local-only audits of robots.txt, sitemaps, metadata, and llms.txt.
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    A Model Context Protocol server that enables AI models to perform real-time internet and knowledge searches through Higress, enhancing model responses with up-to-date information from Google, Bing, Arxiv, and internal knowledge bases.
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    Apache 2.0
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    An MCP server that integrates X (Twitter) API access with Grok-powered intelligence for real-time social media analysis and account management. It provides tools for reading and writing tweets, managing direct messages, and generating AI-powered topic summaries or daily briefings.
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    A read-only MCP server that provides document awareness for agents by parsing local files into structured profiles, blocks, chunks, and search results, enabling agents to understand and cite document content without dealing with raw file formats.
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    Enables AI agents to interact with the AI-Archive platform for research paper discovery through semantic search, paper submission and management, peer review with structured scoring, and citation generation in multiple formats.
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    Personal multi-LLM memory repository using Markdown as source of truth, SQLite FTS5 for retrieval, and MCP tools for search, context, and write proposals.
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    Advanced content gap analysis using Query Decomposition and Keyword Fan-Out (Google's patented methodology). Tells you exactly what user queries your content covers - and what it misses. Built on academic research because I needed to understand how AI search engines actually evaluate content.
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    Apache 2.0
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    GEO (Generative Engine Optimisation). This tool shows you exactly how AI search engines see your content - claim density, writing quality, E-E-A-T signals, extractability. Research-backed metrics that correlate with 40% higher AI citation rates.
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    MIT