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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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    Enables read-only interaction with Snowflake databases through SQL queries, schema exploration, and data insight tracking. Provides tools to query data, list databases/schemas/tables, describe table structures, and maintain a memo of discovered insights.
    GPL 3.0
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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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    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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    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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    A read-only MCP server that reports BI pipeline readiness, blockers, and the next allowed action for governed Power BI workflows. It never writes files, executes warehouse work, or grants human approvals.
    6
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    Apache 2.0
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    An MCP server that provides safe, read-only access to a PostgreSQL warehouse, enabling schema introspection, guarded SQL queries, and truncated result reporting for LLMs.
    3
    MIT
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    Answers "sales dropped since last week — where?" by comparing a target period against a weekday-adjusted baseline and localizing which attribute combinations (e.g. channel=web, or Tuesday nights) explain the shift. Runs fully offline on your own CSV — no API key, no ML training, read-only.
    2
    MIT
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    Turns a folder of CSV, Parquet, and JSON files into a single SQL-queryable source for AI agents, supporting JOINs across files with read-only sandboxed access.
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    MIT