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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.
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    MIT
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    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.
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    Apache 2.0
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    Enables AI assistants to interact with Databar.ai's data enrichment API, allowing discovery, configuration, and execution of data enrichments across hundreds of providers using natural language.
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    Integrates with the Datalog Studio REST API to explore projects, tables, and assets within a workspace. It enables users to understand data schemas and upload plain text content directly for AI processing.
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    BSD 3-Clause
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    Eunomia MCP Server is an extension of the Eunomiaframework that connects Eunomia instruments with servers. It provides a simple way to orchestrate data governance policies (like PII detection or user access control) and seamlessly integrate them with external serve
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    Apache 2.0
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    Enables natural language data analysis on uploaded CSV files by converting them to SQLite and exposing read-only database tools via MCP. Integrates with Ollama LLM to translate user questions into safe SQL queries.
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    Enables interaction with Real Canadian Superstore to extract order history, browse products, and export purchase data. Supports authentication via bearer token and provides comprehensive order management and product discovery capabilities.
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    A Model Context Protocol (MCP) server that integrates the FAIM time series forecasting SDK with any MCP-compatible AI assistant, enabling AI-powered forecasting capabilities.
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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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    MCP server for chatting with physical-world data from robotics, drones, automotive, and IoT sources using natural language. It generates auditable SQL queries over Apache Arrow/DuckDB to let you analyze, summarize, and build data pipelines.
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    Apache 2.0