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"iOS" matching MCP servers:

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    Enables AI assistants to manage Xcode projects by listing targets, reading configurations, and triggering builds via the Model Context Protocol. It facilitates natural language interaction with macOS developer tools to streamline iOS app development processes.
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    MIT
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    Enables AI assistants to build, test, run, and manage Apple platform projects (iOS, macOS, tvOS, watchOS, visionOS) directly through Xcode. Provides comprehensive control over Xcode projects, Swift packages, simulators, and development workflows without leaving your editor.
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    A Model Context Protocol server that provides tools for Xcode-related operations, making it easier to work with iOS project management, building, testing, archiving, and deploying apps to both simulators and physical devices.
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    An MCP server that enables AI agents to execute Lua code, inspect scripts, spy on remotes, and interact with running Roblox game clients, including support for mobile executors on Android and iOS.
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    Enable Claude Code, Cursor, or your favorite LLM to interact with Xcode, building your projects the same way you do, and seeing the same errors. Greatly increases productivity when working on iOS, iPadOS, macOS, visionOS, tvOS projects & Swift packages - or any time you might use Xcode.
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    A demonstration server that reveals security risks by accessing sensitive environment variables, illustrating how MCP tools can potentially leak user data without explicit consent.
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    A Model Context Protocol server that automatically reads the Claude Desktop configuration file and presents all available MCP services in an easy-to-copy format at the top of the tools list.
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    Enables AI agents to create, manage, and execute code in isolated Firecracker microVM sandboxes via the MCP protocol, with support for sandbox lifecycle and file operations.
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    Apache 2.0
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    Arithym — lightweight precision math for agents on the go. Exact arithmetic MCP server with 62 tools, zero hallucination, sub-millisecond computation and is 61% cheaper than Python code execution at scale.