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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.
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    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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    Enables automatic creation and management of weekly work reports in Korean through structured templates. Organizes work tasks and issues with automatic file management, backup/rollback, and 100% template compliance through JSON Schema validation.
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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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    Enables comprehensive content management through Markdown processing, HTML rendering, intelligent fuzzy search, and document analysis. Supports frontmatter parsing, tag-based filtering, table of contents generation, and directory statistics for efficient content organization and discovery.
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    MIT
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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.
    3
    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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    Enables comprehensive content analysis through web scraping, document processing (PDF, DOCX, TXT, RTF), screenshot analysis, and local Excel database management. Provides intelligent workflows for extracting, analyzing, and storing content from multiple sources with automated categorization and search capabilities.
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    ISC
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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