"Xcode" matching MCP servers:

Unified MCP server for Xcode + iOS Simulator — build, deploy, screenshot, and interact with your iOS app from Claude Code, Cursor, or any MCP client. Built in Swift. Single binary. No Node/Python runtime required.

A Model Context Protocol server that enables AI assistants to build and test Xcode projects directly through a standardized interface, with capabilities for running tests, monitoring progress, and accessing logs in real-time.

A comprehensive MCP server for iOS/macOS development that gives AI assistants full control over Xcode build, test, simulator management, and app deployment.

Connects AI coding clients like OpenCode, Codex, and Claude Code to Xcode and Apple development tools, enabling builds, tests, simulator and device management, profiling, asset handling, and more through natural language.

MCP server for Xcode build automation and log parsing that opens Xcode projects, triggers builds directly in Xcode, and parses build logs to extract errors and warnings.

Enables AI coding tools to run CheckMyLaunch scans on GitHub repos or live URLs and retrieve findings and repair prompts directly within the chat.

AI-powered continuous code assistant for Cursor, VS Code, Antigravity, and Claude Code via MCP, providing tools for code review, testing, documentation, and quality analysis.

Enables AI assistants to perform comprehensive code reviews of local uncommitted changes by combining git diffs with static analysis from linters like ESLint and TypeScript. Returns structured JSON feedback with findings, suggestions, and quality assessments powered by Google's Gemini CLI.

Connects AI coding assistants to PyCharm's code quality inspections and optionally SonarQube for IDE, providing unified, de-duplicated code analysis results without uploading source code.

Enables AI assistants to access TestFlight beta tester feedback, including screenshots, crash logs, and text comments from App Store Connect. It works across any platform without requiring Xcode, using official API keys and optional browser automation for full text feedback.

One MCP endpoint, 43 tools for iOS-simulator E2E — native UI automation, Maestro flows, trustworthy oracle-ladder assertions, WebView DOM + network (JSON/HAR), and React Native debugging (Metro logs/network/state). macOS + Xcode.

MCP server that drives Safari on a physically attached iPhone via Apple's safaridriver, enabling navigation, screenshots, DOM snapshots, console logs, network timings, and tap/type/scroll actions on the real device. No Xcode, Appium, or WebDriverAgent required.

Enables MCP-compatible agents to audit an entire repository through one question, detecting stacks and running parallel checks for dead code, dependencies, security, CVEs, complexity, and lint across Laravel/PHP, Python, TypeScript/React, and Flutter/Dart. It returns normalized, severity-sorted findings with false positives flagged and secret values kept out of the output.

Scaffolds new MCP servers for the OpenSIN-Code ecosystem with templates for Python, Node, Go; provides tools to add tools, test, validate, register, publish, and audit servers.

A lightweight, configurable server that fetches coding guidelines, security rules, and validation patterns from external sources to help development teams maintain code quality standards in WordPress projects.

Provides 28 MCP tools across 16 analysis engines for comprehensive Python code quality assessment, including complexity scoring, security scanning, dead code detection, dependency auditing, and test quality analysis.

AI-powered code review tool that detects AI-generated code defects invisible to traditional linters — hallucinated packages, deprecated APIs, cross-file contradictions, hidden security anti-patterns, and over-engineering. Works as a standalone CLI, GitHub Action, or MCP server. Supports TypeScript, Python, Java, Go, and Kotlin. Free for individuals, no API key required.

Hybrid code quality analysis server combining fast logic-based checks with AI-powered deep analysis, offering tools for summaries, quick wins, and trend tracking.

Enables LLMs to access AST-based code structure maps, token-efficient skeletons, and analyze diff impact and blast radius for regression testing.

Enables auditing codebases for production readiness, including linting, testing, CI/CD, security, branch conventions, architecture, and an A–F quality scorecard via MCP tools.