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    About AI/ML-powered diagnostic engine for SRE Observability on Konflux and OpenShift. It uses the Model Context Protocol (MCP) and 40+ tools to analyze logs, metrics, and traces, enabling automated RCA and predictive analysis.
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    Apache 2.0
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    A server implementing Anthropic's Model Context Protocol (MCP) for Firebird SQL databases, enabling Claude and other LLMs to securely access, analyze, and manipulate data in Firebird databases through natural language.
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    MIT
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    A secure server that enables AI applications to execute shell commands in specified directories, supporting multiple shell types (bash, sh, cmd, powershell) with built-in security features like directory isolation and timeout control.
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    Apache 2.0
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    Enables AI assistants to manage MySQL databases through natural language commands. Supports database operations, table management, data queries, and import/export functionality with built-in security features.
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    MIT
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    Enables AI assistants to execute security testing tools on a Kali Linux machine over SSH, including reconnaissance, web app scanning, and static/dynamic analysis.
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    MIT
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    Enables Claude to execute PowerShell commands and scripts in a persistent interactive terminal on Windows, with real-time output streaming to a web terminal.
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    MIT
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    A desktop launcher and local MCP workspace server that enables ChatGPT and other MCP clients to securely read, edit, search, run commands, and show changes in selected local project folders.
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    MIT
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    A human-in-the-loop SSH bridge for AI agents that requires approval for every command before execution on configured servers.
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    MIT
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    AI sidecar terminal — let Claude/Cursor run commands in a visible, persistent terminal you control.
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    MIT
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    A local MCP server that gives Claude in the browser tools to interact with a Fedora machine, including file operations, system diagnostics, build tasks, and root actions via Polkit.
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    MIT
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    Enables LLM agents to execute arbitrary Python code in secure, isolated sandbox environments with automatic dependency management and file handling. Each code execution runs in a fresh virtual environment that gets destroyed after completion, providing safe and reproducible Python code execution.
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    MIT