Xcodeproj MCP Server

The xcodeproj‑mcp-server brings Xcode project manipulation into the world of Model Context Protocol (MCP) by exposing a rich set of tools that let AI assistants and other clients work directly with files. By leveraging the robust library, the server guarantees that all changes are written in a consistent and error‑free manner while still offering the flexibility needed for complex workflows. This eliminates the need to open Xcode or manually edit project files, thereby reducing friction for developers who rely on automation and AI‑driven code generation.

At its core, the server provides a comprehensive API for creating new projects, managing targets, files, and build configurations, as well as inspecting the hierarchical structure of groups and sub‑projects. Developers can programmatically add dependencies, frameworks, and custom build phases such as SwiftLint or code formatters. The ability to scaffold multi‑target setups—including apps, frameworks, tests, and extensions—means that even large, modular projects can be initialized or updated with a single command issued from an AI assistant. This is especially valuable for continuous integration pipelines, onboarding new team members, or rapidly prototyping feature branches.

Key capabilities include:

• Project creation and scaffolding: Generate fully‑configured projects with custom bundle identifiers, organization names, and deployment targets.
• Target and file management: Add Swift files or folder references to the appropriate target, ensuring that new code is compiled automatically.
• Build phase automation: Insert post‑build scripts, formatters, or linters into any target without manual configuration.
• Configuration and dependency handling: Set Info.plist values, provisioning profiles, system framework links, and inter‑target dependencies programmatically.
• Inspection utilities: Retrieve the current group hierarchy, target list, and build settings for analysis or transformation by an AI model.

Real‑world scenarios where this server shines include automated code generation workflows, where a language model produces new Swift files and then immediately registers them in the project; CI/CD pipelines that need to adjust build settings or add test targets on the fly; and rapid prototyping environments where developers can spin up a multi‑module project with a single command. By integrating seamlessly into MCP clients, the server allows AI assistants to act as full‑blown project managers—suggesting best practices, correcting configuration errors, and ensuring that every change is reflected across the entire project structure.