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"Linux-compatible version of Cursor" matching MCP servers:

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    Gives coding agents the exact installed version of each dependency in a project from node_modules and lockfile, preventing deprecated API usage by grounding them in reality.
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    MIT
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    A Linux system monitoring MCP server that provides real-time information on CPU, memory, disk, network, processes, Docker, security, and more via MCP tools.
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    MIT
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    Provides AI assistants with the ability to control Linux desktop environments through tools for file management, application launching, and system operations like clipboard access. It includes a multi-level security model to manage permissions for safe, elevated, and restricted actions.
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    Enables full Linux desktop control including windows, mouse, keyboard, clipboard, audio, screenshots, OCR, accessibility, and system management through MCP-compatible AI agents.
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    Enables remote control of the Cursor AI agent via chat platforms like GitHub Issues or Telegram, allowing users to start sessions and receive summaries and prompts in a chat thread.
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    MIT
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    Enables MCP clients like Claude Code and Codex to delegate coding tasks to Cursor's CLI agent, which implements changes in the workspace and returns clean, structured results for review.
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    MIT
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    Provides MCP tools to search, retrieve, and answer questions from the public Open Finance Brasil Confluence documentation using BM25-based local indexing.
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    MIT
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    Give Claude Desktop full desktop control on Linux/X11: screenshot, mouse, keyboard, windows, clipboard, app launch. Zero-dependency MCP extension, MIT-licensed.
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    MIT
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    An MCP server that lets Claude spawn Cursor subagents as async, bounded workers, enabling non-blocking task delegation with asynchronous completion notifications.
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    Enables AI assistants to perform controlled Linux system administration tasks like reading logs, managing services, cron jobs, WordPress, and executing sandboxed Python code, with strict security constraints.
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    GPL 2.0
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    Enables any MCP-compatible AI tool to read and leverage Cursor's context files (rules, agents, and skills) with their activation logic, allowing teams to maintain a single source of context across different AI coding assistants.
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    MIT
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    Enables interactive feedback with image support in Cursor, allowing users to paste images for visual context and feedback.
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    MIT
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    Enables LLMs to execute shell commands and perform file operations on a Linux system, exposing tools like execute_command, read_file, write_file, and more.
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