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"Diagnosing Issues with My Remote Ubuntu Server Configuration" matching MCP servers:

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    Exposes Aniket Charjan's resume as a queryable API for AI assistants, implementing MCP tools, resources, and prompts for detailed resume queries.
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    MIT
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    A secure file management MCP server enabling file operations like listing, reading, creating, renaming, moving, copying, deleting, and searching within a restricted workspace.
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    MIT
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    A TypeScript MCP server boilerplate providing example tools and resources for rapid development of custom Model Context Protocol servers.
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    A Model Context Protocol server built with FastMCP that enables dynamic tool loading and configuration from individual Python files. It provides a flexible framework for automatically discovering, testing, and running tools via Stdio or HTTP transport modes.
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    An MCP server that enables large language models to connect to remote servers via SSH, execute commands, and transfer files securely.
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    Apache 2.0
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    Vision-capable MCP server for controlling Amazon Fire TV through Home Assistant, providing screenshot-guided observation, remote commands, and app/URI actions via authenticated REST calls.
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    MIT
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    Enables natural language interaction with Unfolded Circle Remote 3/Remote Two for configuration, button mapping, UI editing, and backup/restore.
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    MIT
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    A template and demonstration project for building, testing, and deploying remote MCP servers using FastMCP and uv. It provides a foundational structure for creating MCP-compliant tools that can be hosted publicly and integrated with LLM agents.
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    A powerful MCP server with 116 practical tools across 9 categories including compression, web, file system, data processing, text, system, utilities, subagent AI, and browser automation.
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    MIT
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    MCP server giving AI agents full SSH access with persistent sessions, structured command output, SFTP file transfer, and port forwarding.
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    MIT
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    Enables AI agents to monitor MetaTrader 5 accounts on remote Windows VPS via SSH, providing read-only access to positions, history, and logs without executing trades.
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    MIT
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    Enables LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.
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