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"A guide for building applications in Microsoft Power Apps" matching MCP servers:

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    Enables AI agents to access and manage project guidelines, documentation, and context through a structured content system with template support and workflow management.
    37
    MIT
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    A beginner-friendly Model Context Protocol (MCP) server that helps users understand MCP concepts, provides interactive examples, and lists available MCP servers. This server is designed to be a helpful companion for developers working with MCP. Also comes with a huge list of servers you can install.
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    Apache 2.0
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    Provides semantic search capabilities over the Plesk Extensions Guide documentation using Retrieval-Augmented Generation (RAG) and vector embeddings. It enables AI assistants to retrieve relevant technical information and answer natural language queries regarding Plesk extension development.
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    Automatically crawls documentation websites, converts them to organized markdown files, and generates condensed cheat sheets. Intelligently categorizes content into tools/APIs and provides local-first access to downloaded documentation.
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    GPL 3.0
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    Provides AI assistants with specialized tools to interact with NIST's Open Security Controls Assessment Language (OSCAL) framework. It enables agents to retrieve schemas, explore models, and generate valid OSCAL documentation for security compliance automation.
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    Apache 2.0
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    The Microsoft Learn Docs MCP Server is a cloud-hosted service that enables clients like GitHub Copilot and other AI agents to bring trusted and up-to-date information directly from Microsoft's official documentation. It is a remote MCP Server using streamable http, which is lightweight for clients t
    1,834
    CC BY-4.0
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    A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.
    MIT
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    Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.
    MIT
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    Enables interaction with Zhejiang University's learning platform (学在浙大 / 智云课堂) via MCP tools, allowing natural language commands to check todos, view schedules, fetch lecture transcripts, and submit homework.
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