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    Enables interaction with Telegram chat history, including text, photos, and documents, via the GramJS MTProto userbot. It provides tools for searching chats, syncing message history, and downloading media files for local analysis.
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    MIT
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    Enables AI agents to discover and access 800TB+ of public geospatial data from Source Cooperative, with tools for listing organizations, products, files, and fuzzy search.
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    MIT
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    Enables LLMs to profile and analyze tabular data files (CSV, Parquet, Excel, JSON) by extracting schema, statistics, data quality issues, and dtype suggestions, returning structured JSON.
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    MIT
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    Connect Claude to your Power BI semantic models. Browse workspaces, tables, and measures, run DAX queries, and get results — with large datasets automatically saved to local CSV files to protect the LLM context window. Includes a query history log for cross-session reuse and auditability.
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    MIT
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    Enables AI assistants to interact with Hadoop Hue for executing SQL queries using Hive, SparkSQL, or Impala and managing HDFS files. It supports directory browsing, file transfers, and exporting query results to CSV through the Model Context Protocol.
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    Creates compact skeleton representations of large JSON files by preserving structure while truncating string values and deduplicating arrays, helping users understand JSON structure without processing the full data payload.
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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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    A tutorial implementation MCP server that enables analysis of CSV and Parquet files. Allows users to summarize data and query file information through natural language interactions.
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    Provides JSON schema generation and filtering tools for LLMs, helping with large JSON files by converting them to TypeScript definitions and extracting specific fields to reduce context size.
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    MIT
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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
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    MIT
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    An MCP server that enables LLMs to generate high-quality SVG charts using matplotlib, supporting various plot types like line, bar, and heatmaps. It provides flexible configuration for dimensions and axis scales, returning either raw SVG content or paths to saved image files.
    Last updated
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    An MCP server that enables AI assistants to load, query, and analyze local CSV files using tools for filtering, aggregation, and grouping. It provides capabilities to describe schemas, calculate statistics, and sample data directly from CSV files.
    Last updated
    6