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"Developing an AI-based web search and blog writer with auto SEO and image integration" matching MCP servers:

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    Enables analyzing SEO page performance using data from Google Search Console, Google Analytics, and PostHog to identify weak CTR, decaying rankings, and other issues, providing actionable recommendations.
    MIT
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    A
    maintenance
    The complete open-source SEO data stack for AI agents, integrating Google Search Console, Google Analytics 4, Bing Webmaster Tools, and Microsoft Clarity with built-in analyst tools like cannibalization check, low-hanging fruit, and content gap analysis, all self-hosted and free.
    MIT
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    D
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    Enables AI to interact with Microsoft Access (.mdb, .accdb) and SQLite 3 databases, including read-only support for Access 97 databases. Supports executing SQL queries, importing/export data from CSV and Excel files, and storing notes about database files.
    MIT
  • F
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    C
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    An MCP server that connects any two systems so an agent can explore both, map between them, and run real data transfers — then shows its working in a run folder you can audit afterwards.
    1
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    50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.
    50
    345 npm
    6
    MIT
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    Exposes local DuckDB pizza sales data as MCP tools for querying store-level and total sales metrics via natural language, enabling local LLMs to perform real-time analytical queries.
    MIT
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    B
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    Connects and cleans data from business systems like CRM, billing, and support, then exposes a read-only MCP tool for an AI assistant to generate revenue-risk reports.
    12 npm
    Apache 2.0
  • F
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    quality
    D
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    Provides stock market data and computes technical indicators like EMA, MACD, and RSI across multiple timeframes using the LongPort API and TA-Lib. It enables users to perform detailed financial analysis and multi-timeframe market reviews through standard MCP tools.
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  • F
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    Enables schema-aware exploration of JSON data by uploading samples, flattening nested structures, and using heuristic search with token overlap and fuzzy matching to find field paths for target names, accelerating ETL and API onboarding workflows.
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  • F
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    Enables AI-assisted CSV data quality profiling through MCP tools, offering analysis reports and quality scores while preserving privacy by processing only aggregated data.
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  • A
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    quality
    C
    maintenance
    Enables LLM agents to interact with the MOSTLY AI Platform for generating synthetic data, including training generators, managing data connectors, executing queries, and generating synthetic datasets with OAuth 2.1 authentication.
    2
    Apache 2.0