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    Enables AI agents to securely use real secrets (API keys, database passwords) by requiring human approval for each release, ensuring secrets never enter the model's context.
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    Apache 2.0
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    Exposes persistent, stateful remote Bash sessions to AI agents via SSH, enabling command execution with preserved working directory and environment.
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    MIT
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    Problem: MCP clients can't efficiently use Xcode CLI tools because the build and simulator listing commands return more than 50k tokens, exceeding MCP limits. Solution: MCP tooling using progressive disclosure with intelligent caching.
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    MIT
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    MCP server that bridges AI assistants with the SUSE Linux ecosystem, enabling safe access to openSUSE Wiki, OBS, and repositories for system management.
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    GPL 3.0
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    SSH Session MCP fills a gap in the MCP ecosystem by offering a persistent shared SSH PTY runtime, not just stateless command execution. It features browser collaboration, input locking, safe/full execution modes, async command tracking, configurable policy rules, and multi-device profiles. Ideal for remote development, embedded systems, infrastructure workflows, and hardware control scenarios.
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    Apache 2.0
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    Enables agents to interact with CLI applications like vim, htop, and gdb by sending key inputs and capturing terminal output through tmux sessions.
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    MIT
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    Enables SSH remote command execution on any host using the system ssh binary, supporting existing configurations like ssh-agent, ProxyCommand, and jump hosts.
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    MIT
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    Enables execution and management of Babashka scripts using the Model Context Protocol, offering features like caching, command history access, and configurable timeouts for enhanced scripting workflows.
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    Enables spawning ephemeral Linux sandbox containers using Docker and executing commands through an interactive TTY interface. Supports collaborative terminal sessions where both AI clients and humans can simultaneously interact with the same container.
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    MIT
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    MCP server that lets AI agents call APIs without ever seeing the credentials, using a local encrypted vault and per-secret allowlist policies for HTTP requests and subprocess environment variables.
    1
    AGPL 3.0