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    Enables interaction with SAP S/4HANA systems via OData, allowing service discovery, metadata exploration, field value retrieval, and CRUD operations through natural language.
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    MCP server for Durable energy trading analytics that connects Claude Desktop to Snowflake data, enabling natural-language queries about spreads, constraints, generators, and prices.
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    This MCP server enables database migration between heterogeneous systems (Oracle, PostgreSQL, SQL Server, Netezza to PostgreSQL or SQL Server) through AI assistants by providing tools for command preview, execution, validation, and workflow suggestions.
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    MIT
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    An MCP Server implementation that integrates the Balldontlie API, to provide information about players, teams and games for the NBA, NFL and MLB.
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    MIT
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    Enables natural-language AI agents to query and manage Couchbase databases via the Model Context Protocol, allowing users to ask plain-English questions about travel data and get SQL++-backed answers.
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    MIT
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    Enables access to the Hugging Face Hub API to search and retrieve information about machine learning models, datasets, and their metadata. Provides comprehensive tools for exploring the Hugging Face ecosystem including model details, dataset information, and parquet file access.
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    Provides a Model Context Protocol interface to MoCo time tracking and project management systems, enabling AI assistants to retrieve work activities, projects, tasks, holidays, and presence data.
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    MIT
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    Enables AI systems to perform full-text and semantic search operations over structured/unstructured data in Azure Cognitive Search, with capabilities for document indexing and management through natural language.
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    ISC
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    MCP server for 1C:Enterprise ERP with 35 tools: metadata inspection, document CRUD, register queries, and BSP integration. First MCP server for Russian ERP systems (300,000+ organizations). JSON-RPC 2.0 compliant BSL implementation.
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    MIT
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    A server that enables LLMs like Claude to interact with Azure Cosmos DB databases through natural language queries, acting as a translator between AI assistants and database systems.
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    MIT
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    Implements the Model Context Protocol (MCP) to provide AI models with a standardized interface for connecting to external data sources and tools like file systems, databases, or APIs.
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    Enables large language models to retrieve up-to-date and correct information about dlt pipelines, datasets, and schemas, improving AI-assisted development.
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    Apache 2.0
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    Enables AI assistants to securely access and interact with Simplicate business data including CRM, projects, timesheets, and invoices through natural language. Supports searching across resources and retrieving detailed information about organizations, contacts, and project data.
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    Enables AI assistants to interact with IBM i systems through SQL tools and authenticated connections. Provides system monitoring, database queries, and performance analysis capabilities with secure token-based authentication and connection pooling.
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    67
    Apache 2.0