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"Using an MCP server to retrieve logs from a terminal for cursor" matching MCP servers:

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    An MCP server for indexing and searching local text files using late-interaction retrieval (ColBERT-style MaxSim), enabling token-level relevance matching.
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    MIT
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    MCP server for querying and analyzing logs from VMware Aria Operations for Logs, enabling log search, incident detection, and vROps correlation.
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    Enables LLMs to explore and analyze UK Government BEIS inspect_ai evaluation logs directly from tools like Claude Code and Cursor. It provides capabilities to list logs, view evaluation summaries, and inspect conversation histories for specific samples.
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    MIT
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    Enables management of visible, interactive terminal sessions across platforms (macOS, Windows, Linux, WSL). Supports creating, executing commands, capturing output, and managing multiple terminal windows simultaneously.
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    MIT
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    Enables AI agents to analyze ROS2 log files across multiple nodes by merging them into a unified timeline and providing smart query tools, without requiring ROS2 installation.
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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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    MCP server for AI agents to send notifications, copy to clipboard, request confirmations, and collect text input from users across their devices.
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    527
    Apache 2.0
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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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    An MCP server that enables users to execute arbitrary shell commands on their local machine and receive the output. It provides a terminal tool for running system commands through MCP-compatible clients using the Python SDK.
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    An MCP server that gives Jan AI terminal and code execution capabilities, enabling shell commands, multi-language code execution, file manipulation, and git operations locally.
    10
    MIT
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    Fetches a URL and returns the main content as clean Markdown, using plain HTTP when possible and headless Chromium for JavaScript-rendered or bot-protected pages.
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    MIT
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    Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.
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    Apache 2.0