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    An open-source MCP server that imports HR CSV data into an in-memory SQLite database for structured querying and metadata retrieval. It enables users to perform read-only SQL queries and structured searches on employee data through natural language.
    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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    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
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    An implementation that integrates with Odoo ERP systems, enabling AI assistants to interact with Odoo data and functionality through the Model Context Protocol.
    MIT
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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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    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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    An MCP server for controlling Fivetran data pipelines. Enables AI assistants to manage syncs, monitor connection status, and control pipelines through natural language.
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    MIT
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    Enables AI agents to manage Databricks Lakeflow jobs by building and uploading Python wheels and triggering runs with specific arguments. It provides a structured way to orchestrate complex data experiments and monitor execution directly on Databricks clusters.
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    This MCP server enables interaction with the Polytomic API to manage data connections, models, and synchronization tasks. It supports both Reverse ETL and ELT operations, allowing users to trigger syncs, monitor execution status, and configure data pipelines.
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    MIT
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    A Model Context Protocol server that integrates Garmin Connect data with LLMs to provide personalized running analysis and training plans. It enables users to monitor performance metrics, manage training loads, and receive data-driven workout suggestions based on health indicators like VO2 Max and recovery status.
    43
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    Enables AI agents to operate a US power-grid data pipeline – ingest, plan, run, and monitor datasets like CAISO, ERCOT, and EIA-930 through MCP tools that mirror the CLI.
    Apache 2.0