XCF Xcode MCP Server

Overview

XCF is a lightweight, Swift‑only Model Context Protocol (MCP) server built to accelerate the development of Xcode projects through AI assistants such as Claude and Cursor. It removes the need for JavaScript or TypeScript tooling by exposing a rich set of file, directory, and Xcode‑specific operations directly over MCP. Developers can therefore ask the assistant to create files, run builds, or analyze Swift code without leaving their IDE, turning natural‑language queries into concrete actions on the file system and Xcode workspace.

Problem Solved

Building and debugging iOS or macOS apps traditionally requires a mix of Xcode, command‑line tools, and manual file manipulation. When working with AI assistants, the workflow often stalls because the assistant lacks direct access to the project’s internal state or build output. XCF solves this friction by providing a single, well‑defined interface that mirrors the full capabilities of Xcode: project detection, document handling, build diagnostics, and even Swift‑specific code analysis—all accessible through a simple MCP protocol. This eliminates the overhead of maintaining separate tooling and lets developers focus on higher‑level design and code quality.

Core Capabilities

• Project Awareness – XCF automatically detects the nearest or accepts explicit paths via environment variables, ensuring that every command targets the correct workspace.
• File & Directory Operations – Read, write, edit, delete files; list or create directories; and perform batch operations with minimal latency.
• Xcode Document Integration – Open, save, close, and modify Xcode documents programmatically, enabling the assistant to manipulate UI elements or storyboard files.
• Build & Run Feedback – Execute or to trigger Xcode builds; errors and warnings are streamed back to the assistant in real time, allowing on‑the‑fly corrections.
• AI‑Powered Fixes – The assistant can propose and apply fixes to compile errors, lint issues, or code smells directly through XCF commands.
• Swift Code Analysis – Run static analysis tools without a full build, providing insights into code quality, potential bugs, or performance bottlenecks.

Use Cases

• Rapid Prototyping – A developer can ask the assistant to scaffold a new view controller, populate it with boilerplate Swift code, and immediately compile it—all without leaving the text editor.
• Continuous Integration – CI pipelines can invoke XCF to run tests and report failures back to an AI‑based reporting tool, streamlining feedback loops.
• Learning & Mentoring – New iOS developers can receive instant, context‑aware suggestions for best practices while the assistant interacts with their project files.
• Cross‑IDE Support – Works seamlessly with VSCode, Cursor, and Claude Desktop, making it a versatile bridge for teams that use multiple editor environments.

Integration Flow

1. Configuration – Add XCF to the MCP configuration file of the chosen AI client (Cursor or Claude).
2. Startup – The assistant launches XCF via the protocol, establishing a persistent communication channel.
3. Command Execution – The assistant sends structured requests (e.g., “create file with boilerplate”) and receives responses or diagnostics.
4. Feedback Loop – Errors from Xcode builds are parsed and relayed to the assistant, which can then offer corrective actions.

This tight integration keeps the developer’s mental context intact while leveraging AI to automate repetitive tasks and surface deeper insights into Swift code.

Distinctive Advantages

• Zero Runtime Dependencies – Written entirely in Swift, XCF requires no external libraries or package managers, simplifying deployment on macOS.
• Project‑Level Security – Environment variables allow fine‑grained control over which project or workspace the assistant can access, mitigating accidental modifications.
• Real‑Time Diagnostics – Unlike generic file‑operation servers, XCF streams compile errors and warnings directly to the assistant, enabling instant remediation.
• AI‑First Design – The server’s command set is intentionally minimal and intuitive, aligning with the conversational style of AI assistants rather than a verbose API.

In sum, XCF transforms an ordinary Swift project into an interactive AI‑driven workspace, reducing friction and unlocking new levels of productivity for developers who rely on Claude, Cursor, or similar tools.