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    Enables AI assistants to search and filter Azure platform updates, including previews, general availability, and retirements, through natural language queries.
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    MIT
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    Enables querying Azure Application Insights logs by order number through natural language. Provides secure access to Azure Monitor logs with comprehensive error handling and rate limiting.
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    MIT
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    Enables natural language exploration of Azure environments by generating and executing KQL queries against Azure Resource Graph. Supports multi-tenant configurations, subscription scoping, and provides direct access to Azure resource information through conversational interactions.
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    Apache 2.0
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    Enables AI assistants to search and retrieve Azure service updates, retirements, and feature announcements using natural language queries with fast local caching.
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    MIT
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    Enables querying Azure retail pricing information, comparing costs across regions and SKUs, estimating usage-based expenses, and discovering Azure services with savings plan information through the Azure Retail Prices API.
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    15
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    Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.
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    MIT
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    Provides retrieval-augmented generation (RAG) capabilities by ingesting various document formats into a persistent ChromaDB vector store. It enables semantic search and retrieval using either OpenAI or Ollama embeddings for processing local files, directories, and URLs.
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    MIT
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    A Cloudflare Worker that transforms Cloudflare AI Search (AutoRAG) instances into an MCP server for querying documentation. It enables AI models to search and retrieve relevant information from custom document sets stored in R2 buckets.
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    Provides AI assistants with real-time access to Azure retail pricing information, enabling price searches, regional cost comparisons, monthly bill estimates, and SKU discovery through natural language queries.
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    MIT
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    Transforms SAP S/4HANA or ECC systems into conversational AI interfaces by exposing all OData services as dynamic MCP tools. Enables natural language interactions with ERP data including querying, creating, updating, and deleting entities through SAP BTP integration.
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    MIT
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    This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Azure Data Catalog (beta): https://www.cdata.com/download/download.aspx?sku=GNZK-V&type=beta
    Last updated
    MIT