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⇱ Techniques and Tools for Data Analysis, Exploration, and Working with Parquet and CSV Files | Glama

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Techniques and Tools for Data Analysis, Exploration, and Working with Parquet and CSV Files

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  • Why this server?

    This server enables LLMs to perform statistical analysis on user data from databases or CSV files.

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    Enables LLMs to perform statistical analysis and generate ML predictions on user data from databases or CSV files through a Model Context Protocol server.
    Last updated
    2

  • Why this server?

    Provides tools for interacting with databases, including PostgreSQL, DuckDB, and Google Cloud Storage Parquet files, all relevant for data analysis.

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    A Model Context Protocol server that provides tools for interacting with databases, including PostgreSQL, DuckDB, and Google Cloud Storage Parquet files.
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    2

  • Why this server?

    An open-source MCP server connecting to SQL databases, CSV, Parquet files, with tools for executing SQL queries and generating data visualizations.

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    An open-source MCP server that connects to various data sources (SQL databases, CSV, Parquet files), allowing AI models to execute SQL queries and generate data visualizations for analytics and business intelligence.
    Last updated
    2
    12
    74
    MIT

  • Why this server?

    Specifically designed for working with Parquet files, a columnar storage format commonly used in data analysis.

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    A powerful MCP (Model Control Protocol) server that provides tools for manipulating and analyzing Parquet files. This server is designed to work with Claude Desktop and offers four main functionalities:
    Last updated
    2
    2

  • Why this server?

    Enables users to upload retail data, analyze trends, optimize inventory, and forecast sales using AI-powered insights.

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    Enables users to preprocess, analyze, and visualize CSV data through comprehensive tools for data manipulation, statistical analysis, and graph generation.
    Last updated
    3

  • Why this server?

    Provides an interface to access Google Analytics Data API, allowing users to retrieve reports and realtime data from Google Analytics 4 properties.

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    Provides an interface to access Google Analytics Data API through Model Context Protocol (MCP), allowing users to retrieve reports and realtime data from Google Analytics 4 properties.
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    12,207
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    MIT

  • Why this server?

    Allows interaction with OceanBase databases, which could involve data exploration and analysis depending on the data stored.

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    A Model Context Protocol server that enables AI assistants to securely interact with OceanBase databases by listing tables, reading data, and executing SQL queries through a controlled interface.
    Last updated
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    3
    Apache 2.0

  • Why this server?

    MCP Server for interacting with Cube semantic layers that provides tools for querying and describing data from Cube deployments.

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    MCP Server for interacting with Cube semantic layers that provides tools for querying and describing data from Cube deployments.
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    12
    GPL 3.0

  • Why this server?

    Allows users to interact with Google Cloud Platform resources including BigQuery which is relevant for data analysis.

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    A Model Context Protocol server that connects to Google Cloud services, allowing users to query logs, interact with Spanner databases, and analyze Cloud Monitoring metrics through natural language interaction.
    Last updated
    40
    162
    78
    Apache 2.0