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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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    Provides secure, read-only PostgreSQL database access via MCP tools like query_inventory and get_top_sales. Blocks dangerous SQL commands while allowing AI to execute controlled SELECT queries.
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    ISC
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    Enables AI-powered natural language stock market queries with real-time data from Yahoo Finance and CSV fallback. Uses Google Gemini to interpret queries and automatically fetch stock prices, comparisons, and market summaries.
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    Enables querying and analyzing user, product, and order data with filtering capabilities and real-time statistics. Supports WebSocket connections to XiaoZhi AI platform with automatic reconnection.
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    Enables querying a hybrid-retrieval RAG pipeline (dense + BM25) over ingested PDF documents, returning answers generated by Gemini.
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    Provides pre-indexed knowledge packs for popular technologies (Stripe, React, etc.) that MCP-compatible agents can subscribe to and search, delivering citation-grounded answers with hourly fresh indexes.
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    Enables agents to perform controlled enterprise data queries through semantic intent, with runtime validation of statistics, filters, granularity, permissions, and physical bindings. Exposes tools like semantic_query for safe, fail-closed access to data horizons and capabilities.
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    Search 1,500+ pre-verified, cited knowledge units across 16 domains. 6 tools: query, batch query, get unit, list domains, suggest topics, report issues. Free, no API key required.
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    MIT
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    Read-only MCP server that lets AI agents safely query SQLite, PostgreSQL, and MySQL/MariaDB. Enforces read-only transactions with column masking, row caps, query timeouts, EXPLAIN-based cost rejection, and rate limiting.
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    MIT
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    Python MCP server for vector search using Qdrant vector database and Ollama embeddings, with advanced query techniques like query expansion, HyDE, and reranking.
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    MIT
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    Enables interaction with MySQL databases (including AWS RDS and cloud instances) through natural language. Supports database connections, query execution, schema inspection, and comprehensive database management operations.
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    MIT
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    A Model Context Protocol (MCP) server that provides read-only TDengine database queries for AI assistants, allowing users to execute queries, explore database structures, and investigate data directly from AI-powered tools.
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    MIT
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    Provides AI models with structured access to Trino's distributed SQL query engine, enabling LLMs to directly query and analyze data stored in Trino databases.
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    MIT
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    Provides database interaction through natural language, enabling query execution and content processing.
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    Apache 2.0