{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-xcodebuildmcp","slug":"xcodebuildmcp","name":"XcodeBuildMCP","type":"mcp","url":"https://github.com/cameroncooke/xcodebuildmcp","page_url":"https://unfragile.ai/xcodebuildmcp","categories":["mcp-servers","testing-quality"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-xcodebuildmcp__cap_0","uri":"capability://automation.workflow.ios.macos.visionos.watchos.app.scaffolding.and.project.generation","name":"ios/macos/visionos/watchos app scaffolding and project generation","description":"Generates new Xcode projects for Apple platforms (iOS, macOS, visionOS, watchOS) by invoking xcodebuild's project creation templates and configuring build settings, target configurations, and platform-specific entitlements. The MCP server wraps native Xcode tooling to expose project generation as callable tools for AI agents, enabling programmatic app initialization without manual Xcode UI interaction.","intents":["I want an AI agent to create a new iOS app project with specific configurations and dependencies","I need to scaffold multiple app variants (iPhone, iPad, Mac) from a single template","I want to generate watchOS or visionOS apps programmatically as part of an automated workflow"],"best_for":["AI agents building iOS/macOS apps autonomously","Teams automating app template generation and onboarding","Developers integrating Xcode workflows into LLM-driven development pipelines"],"limitations":["Requires Xcode to be installed and configured on the host machine — cannot run on Linux or Windows","Project generation inherits Xcode's template limitations — custom templates require manual Xcode setup","No support for CocoaPods or SPM dependency injection during scaffolding — must be added post-generation"],"requires":["macOS 12.0+","Xcode 13.0+ with command-line tools installed","xcodebuild CLI available in PATH"],"input_types":["structured parameters (project name, bundle ID, platform, language)","template selection (iOS App, macOS App, etc.)"],"output_types":["Xcode project directory structure","build.log with project creation status"],"categories":["automation-workflow","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-xcodebuildmcp__cap_1","uri":"capability://automation.workflow.xcode.build.execution.with.target.and.configuration.selection","name":"xcode build execution with target and configuration selection","description":"Executes xcodebuild commands with support for specifying build targets, schemes, configurations (Debug/Release), and destination platforms (simulator/device). The MCP server captures build output, logs, and exit codes, streaming real-time compilation feedback to the AI agent. Supports parallel builds, build caching, and incremental compilation through xcodebuild's native optimization flags.","intents":["I want an AI agent to build an iOS app for a specific simulator or device and report build errors","I need to trigger Release builds with code signing and provisioning profiles configured","I want to build multiple targets in parallel and aggregate build status across the project"],"best_for":["AI agents automating iOS/macOS CI/CD pipelines","Developers integrating Xcode builds into LLM-driven testing workflows","Teams running headless builds on macOS CI runners (GitHub Actions, GitLab CI)"],"limitations":["Build performance depends on local machine resources — no distributed compilation support","Code signing and provisioning profiles must be pre-configured on the host — cannot be injected via MCP parameters","Build logs are captured as plain text — no structured parsing of compiler warnings/errors into machine-readable format"],"requires":["macOS 12.0+","Xcode 13.0+ with command-line tools","Valid provisioning profiles and code signing certificates for device builds","Sufficient disk space for build artifacts"],"input_types":["build parameters (scheme, configuration, destination, derived data path)","environment variables for build customization"],"output_types":["build.log with compilation output","exit code (0 for success, non-zero for failure)","build artifacts (app bundle, dSYM files)"],"categories":["automation-workflow","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-xcodebuildmcp__cap_10","uri":"capability://data.processing.analysis.code.coverage.analysis.and.reporting","name":"code coverage analysis and reporting","description":"Collects and analyzes code coverage data from test execution, generating coverage reports showing line/branch coverage percentages by file and function. Integrates with Xcode's coverage collection to capture coverage metrics during test runs. The MCP server parses coverage data and provides structured reports identifying untested code paths.","intents":["I want an AI agent to measure code coverage after running tests and identify untested code","I need to track coverage trends over time and detect regressions","I want to generate coverage reports for specific test targets or files"],"best_for":["AI agents analyzing test quality and identifying coverage gaps","Teams tracking code coverage metrics and enforcing coverage thresholds","Developers integrating coverage analysis into LLM-driven QA workflows"],"limitations":["Coverage collection adds overhead to test execution — may slow tests by 10-20%","Coverage data is only available for code compiled with coverage instrumentation — requires rebuild","Coverage reports are limited to line/branch coverage — no path or mutation coverage"],"requires":["macOS 12.0+","Xcode 13.0+ with coverage support","Tests compiled with coverage instrumentation enabled","Test execution on simulator or device"],"input_types":["test target or test class/method name","coverage report format (JSON, HTML, text)"],"output_types":["coverage metrics (line coverage %, branch coverage %)","coverage by file (file name, coverage %)","coverage by function (function name, coverage %)","uncovered code paths"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-xcodebuildmcp__cap_11","uri":"capability://data.processing.analysis.app.performance.profiling.and.metrics.collection","name":"app performance profiling and metrics collection","description":"Collects runtime performance metrics from running iOS/macOS apps including CPU usage, memory consumption, frame rate, and energy impact. Uses Instruments framework integration and system metrics APIs to gather performance data during app execution. The MCP server aggregates metrics and provides structured performance reports for AI agents to analyze.","intents":["I want an AI agent to monitor app performance during testing and detect performance regressions","I need to measure CPU, memory, and energy usage to identify optimization opportunities","I want to capture frame rate and rendering performance metrics"],"best_for":["AI agents analyzing app performance and detecting regressions","Teams automating performance testing and benchmarking","Developers integrating performance analysis into LLM-driven QA workflows"],"limitations":["Performance profiling adds overhead to app execution — may affect measured metrics","Metrics collection requires running app on simulator or device — no static analysis","Some metrics (energy impact) are only available on physical devices, not simulators"],"requires":["macOS 12.0+","Xcode 13.0+ with Instruments framework","Running app on simulator or connected device","Sufficient system resources for profiling overhead"],"input_types":["app process ID or bundle identifier","metrics to collect (CPU, memory, frame rate, energy)","collection duration"],"output_types":["performance metrics (CPU %, memory MB, FPS, energy impact)","metric timeseries (timestamp, value pairs)","performance summary (average, peak, min values)"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-xcodebuildmcp__cap_12","uri":"capability://data.processing.analysis.crash.log.capture.and.analysis","name":"crash log capture and analysis","description":"Captures crash logs from iOS/macOS apps running on simulators or physical devices, parsing crash stack traces and extracting exception information. The MCP server retrieves crash logs from system log storage, parses symbolicated stack traces, and provides structured crash reports with exception type, message, and call stack. Supports filtering crashes by app bundle identifier or time range.","intents":["I want an AI agent to detect app crashes during testing and analyze crash stack traces","I need to capture crash logs and identify the root cause of failures","I want to track crash frequency and identify recurring crash patterns"],"best_for":["AI agents detecting and analyzing app crashes during automated testing","Teams automating crash detection and root cause analysis","Developers integrating crash analysis into LLM-driven QA workflows"],"limitations":["Crash logs are only available after app termination — cannot capture crashes in real-time","Stack traces require symbolication — unsymbolicated crashes are difficult to analyze","Crash log retention is limited by system storage — old crashes may be automatically deleted"],"requires":["macOS 12.0+","Xcode 13.0+ with command-line tools","App must have crashed on simulator or connected device","dSYM files for symbolication (optional but recommended)"],"input_types":["app bundle identifier","time range for crash filtering","crash type filter (exception, signal, etc.)"],"output_types":["crash logs (text format)","structured crash report (exception type, message, stack trace)","crash metadata (timestamp, app version, OS version)"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-xcodebuildmcp__cap_2","uri":"capability://automation.workflow.ios.macos.simulator.lifecycle.management.and.control","name":"ios/macos simulator lifecycle management and control","description":"Manages iOS/macOS simulator instances by launching, stopping, resetting, and querying simulator state through xcodebuild and simctl CLI tools. Supports selecting specific simulator types (iPhone 15 Pro, iPad Air, etc.), managing multiple concurrent simulators, and configuring simulator environment variables. The MCP server maintains simulator state and provides tools for AI agents to control simulator behavior programmatically.","intents":["I want an AI agent to launch a specific iOS simulator and verify it's ready for testing","I need to reset a simulator to a clean state between test runs","I want to manage multiple simulators concurrently and run tests in parallel"],"best_for":["AI agents automating iOS app testing workflows","Teams running parallel test suites on multiple simulator instances","Developers integrating simulator management into LLM-driven QA pipelines"],"limitations":["Simulator performance is limited by host machine resources — cannot run more simulators concurrently than available CPU/RAM","Simulator state is ephemeral — resets wipe all app data and settings, requiring re-setup between test runs","No support for custom simulator skins or hardware configurations beyond standard Apple device types"],"requires":["macOS 12.0+","Xcode 13.0+ with iOS/macOS simulators installed","Sufficient RAM (minimum 8GB recommended for multiple simulators)"],"input_types":["simulator identifier (e.g., 'iPhone 15 Pro', 'iPad Air')","action (launch, stop, reset, erase)","environment variables for simulator configuration"],"output_types":["simulator state (booted, shutdown, creating)","UDID (unique device identifier)","available simulators list"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-xcodebuildmcp__cap_3","uri":"capability://automation.workflow.app.installation.and.launch.on.simulators.and.physical.devices","name":"app installation and launch on simulators and physical devices","description":"Installs compiled app bundles (.app or .ipa files) onto iOS/macOS simulators or connected physical devices, then launches the app with optional command-line arguments and environment variables. Uses xcodebuild and simctl to handle installation and launch, supporting both Debug and Release builds. Captures app launch logs and process IDs for subsequent monitoring.","intents":["I want an AI agent to install a built app on a simulator and launch it automatically","I need to install an app on a physical device and pass custom launch arguments for testing","I want to launch the same app on multiple devices in parallel and capture launch logs"],"best_for":["AI agents automating end-to-end iOS/macOS testing workflows","Teams running automated app deployment and smoke tests","Developers integrating app installation into LLM-driven QA pipelines"],"limitations":["Physical device installation requires valid provisioning profiles and code signing — cannot install unsigned or mismatched bundles","App launch arguments are passed as command-line parameters — no support for deep linking or URL schemes configuration","No built-in app state management — AI agents must track app lifecycle separately"],"requires":["macOS 12.0+","Xcode 13.0+ with command-line tools","Compiled app bundle (.app for simulator, .ipa for device)","Physical devices must be connected via USB and trusted"],"input_types":["app bundle path (.app or .ipa)","destination (simulator UDID or device identifier)","launch arguments and environment variables"],"output_types":["installation status (success/failure)","app process ID (PID)","launch logs"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-xcodebuildmcp__cap_4","uri":"capability://automation.workflow.runtime.log.capture.and.streaming.from.running.apps","name":"runtime log capture and streaming from running apps","description":"Captures and streams real-time logs from running iOS/macOS apps using os_log framework integration and system log aggregation. The MCP server tails app logs, filters by log level (debug, info, warning, error), and streams output to the AI agent. Supports filtering by subsystem, category, and process ID to isolate app-specific logs from system noise.","intents":["I want an AI agent to monitor app logs in real-time and detect crashes or errors","I need to capture debug logs from a running app and analyze them for performance issues","I want to filter logs by subsystem to isolate network requests or database operations"],"best_for":["AI agents debugging iOS/macOS app behavior during automated testing","Teams analyzing app logs for performance regressions or crashes","Developers integrating log analysis into LLM-driven troubleshooting workflows"],"limitations":["Log capture requires the app to be running — cannot retrieve historical logs after app termination","System log access requires elevated permissions on some macOS versions — may require sudo","Log filtering is basic (subsystem, category, level) — no regex or complex query support"],"requires":["macOS 12.0+","Xcode 13.0+ with command-line tools","Running app on simulator or connected device","App must use os_log or NSLog for logging"],"input_types":["app process ID or bundle identifier","log level filter (debug, info, warning, error)","subsystem and category filters"],"output_types":["log stream (text lines with timestamps)","structured log entries (timestamp, level, subsystem, message)"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-xcodebuildmcp__cap_5","uri":"capability://image.visual.screenshot.capture.and.visual.state.inspection","name":"screenshot capture and visual state inspection","description":"Captures screenshots from running iOS/macOS apps on simulators or physical devices, saving images in PNG format with metadata (resolution, device type, timestamp). Supports capturing full-screen screenshots or specific UI regions. Screenshots are returned as file paths or base64-encoded data, enabling AI agents to perform visual regression testing or UI validation.","intents":["I want an AI agent to capture screenshots during app testing and compare them against baseline images","I need to verify UI layout and visual appearance across different device sizes and orientations","I want to capture screenshots at specific app states for visual regression detection"],"best_for":["AI agents performing visual regression testing on iOS/macOS apps","Teams automating UI validation and screenshot comparison","Developers integrating visual testing into LLM-driven QA workflows"],"limitations":["Screenshots are static images — no support for video recording or animation capture","Visual comparison requires external image processing tools — no built-in diff or similarity scoring","Screenshot capture may include system UI elements (status bar, home indicator) depending on simulator/device"],"requires":["macOS 12.0+","Xcode 13.0+ with command-line tools","Running app on simulator or connected device","Sufficient disk space for screenshot storage"],"input_types":["app process ID or bundle identifier","screenshot region (full-screen or coordinates)","output format (PNG, base64)"],"output_types":["PNG image file","base64-encoded image data","image metadata (resolution, device type, timestamp)"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-xcodebuildmcp__cap_6","uri":"capability://data.processing.analysis.accessibility.hierarchy.inspection.and.ui.element.querying","name":"accessibility hierarchy inspection and ui element querying","description":"Inspects the accessibility hierarchy of running iOS/macOS apps, exposing UI element properties (label, identifier, frame, accessibility traits) as structured data. The MCP server queries the app's accessibility tree using XCTest's XCUIApplication API, enabling AI agents to locate and interact with UI elements programmatically. Supports filtering by element type, accessibility label, or identifier.","intents":["I want an AI agent to find a button or text field by accessibility label and determine its position","I need to inspect the full UI hierarchy to understand app structure and identify interactive elements","I want to query for elements matching specific accessibility traits (button, text field, etc.)"],"best_for":["AI agents performing UI automation and element interaction on iOS/macOS apps","Teams automating accessibility testing and compliance verification","Developers integrating UI inspection into LLM-driven testing workflows"],"limitations":["Accessibility hierarchy is only available for apps running on simulators or devices with XCTest support — not available for background processes","Element properties are limited to accessibility attributes — custom UI properties are not exposed","Hierarchy inspection may be slow for complex UIs with thousands of elements"],"requires":["macOS 12.0+","Xcode 13.0+ with XCTest framework","Running app on simulator or connected device","App must have accessibility support enabled"],"input_types":["app process ID or bundle identifier","query filters (element type, label, identifier)","hierarchy depth (full tree or specific subtree)"],"output_types":["structured accessibility tree (JSON or XML)","element properties (label, identifier, frame, traits)","element hierarchy (parent-child relationships)"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-xcodebuildmcp__cap_7","uri":"capability://automation.workflow.ui.element.interaction.and.gesture.simulation","name":"ui element interaction and gesture simulation","description":"Simulates user interactions (tap, swipe, type, scroll) on iOS/macOS app UI elements by sending XCTest events to the running app. Supports targeting elements by accessibility label, identifier, or coordinates. Gestures are executed with configurable duration and velocity, enabling realistic interaction simulation. The MCP server tracks interaction results and captures any errors or state changes.","intents":["I want an AI agent to tap a button or text field and verify the app responds correctly","I need to simulate complex gestures (swipe, pinch, long-press) for testing gesture-based interactions","I want to type text into text fields and verify input validation"],"best_for":["AI agents performing end-to-end UI testing on iOS/macOS apps","Teams automating user interaction flows and regression testing","Developers integrating gesture testing into LLM-driven QA workflows"],"limitations":["Gesture simulation is limited to XCTest-supported interactions — custom gestures or multi-touch sequences may not be fully supported","Interaction timing is approximate — precise timing-dependent interactions may be unreliable","No support for hardware interactions (camera, microphone, sensors) — only UI-level interactions"],"requires":["macOS 12.0+","Xcode 13.0+ with XCTest framework","Running app on simulator or connected device","App must have accessibility support enabled for element targeting"],"input_types":["interaction type (tap, swipe, type, scroll, long-press)","target element (accessibility label, identifier, or coordinates)","interaction parameters (duration, velocity, text)"],"output_types":["interaction status (success/failure)","app state after interaction (screenshot, logs)","error messages if interaction fails"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-xcodebuildmcp__cap_8","uri":"capability://automation.workflow.test.execution.and.result.reporting","name":"test execution and result reporting","description":"Executes XCTest test suites on iOS/macOS apps using xcodebuild's test command, capturing test results, failures, and performance metrics. Supports running specific test classes, methods, or entire test targets. The MCP server parses test output, aggregates results (pass/fail counts), and provides structured test reports with failure details and stack traces.","intents":["I want an AI agent to run a test suite and report which tests passed or failed","I need to execute specific test methods and capture detailed failure information","I want to run tests on multiple devices/simulators in parallel and aggregate results"],"best_for":["AI agents automating iOS/macOS test execution and result analysis","Teams running continuous testing pipelines with automated failure detection","Developers integrating test automation into LLM-driven QA workflows"],"limitations":["Test execution time depends on test complexity and device performance — no built-in test parallelization across devices","Test results are captured as text output — no structured test report format (JUnit XML, etc.)","Flaky tests may produce inconsistent results — no built-in retry or stability analysis"],"requires":["macOS 12.0+","Xcode 13.0+ with XCTest framework","XCTest test targets defined in Xcode project","Running simulator or connected device for test execution"],"input_types":["test target or test class/method name","destination (simulator UDID or device identifier)","test configuration (Debug/Release)"],"output_types":["test results (pass/fail counts)","failure details (test name, error message, stack trace)","test execution time","coverage metrics (if enabled)"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-xcodebuildmcp__cap_9","uri":"capability://data.processing.analysis.device.and.simulator.enumeration.and.status.querying","name":"device and simulator enumeration and status querying","description":"Lists available iOS/macOS simulators and connected physical devices, querying their status (booted, shutdown), capabilities (supported iOS versions, device type), and hardware specifications. Uses simctl and xcodebuild to enumerate devices and parse their properties. Provides AI agents with a current inventory of available testing targets.","intents":["I want an AI agent to discover available simulators and devices before running tests","I need to check if a specific device is available and ready for testing","I want to query device capabilities to determine which tests can run on which devices"],"best_for":["AI agents making intelligent decisions about test target selection","Teams automating device allocation and test distribution","Developers integrating device discovery into LLM-driven testing workflows"],"limitations":["Device list is static at query time — changes (new simulators, device connections) require re-querying","Physical device status may be delayed — USB connection state may not be immediately reflected","No support for querying device storage, battery, or network status"],"requires":["macOS 12.0+","Xcode 13.0+ with command-line tools","Physical devices must be connected via USB for enumeration"],"input_types":["device type filter (simulator, device, all)","platform filter (iOS, macOS, watchOS, visionOS)"],"output_types":["device list (JSON or structured format)","device properties (UDID, name, OS version, device type, status)","device capabilities (supported iOS versions, hardware features)"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":36,"verified":false,"data_access_risk":"moderate","permissions":["macOS 12.0+","Xcode 13.0+ with command-line tools installed","xcodebuild CLI available in PATH","Xcode 13.0+ with command-line tools","Valid provisioning profiles and code signing certificates for device builds","Sufficient disk space for build artifacts","Xcode 13.0+ with coverage support","Tests compiled with coverage instrumentation enabled","Test execution on simulator or device","Xcode 13.0+ with Instruments framework"],"failure_modes":["Requires Xcode to be installed and configured on the host machine — cannot run on Linux or Windows","Project generation inherits Xcode's template limitations — custom templates require manual Xcode setup","No support for CocoaPods or SPM dependency injection during scaffolding — must be added post-generation","Build performance depends on local machine resources — no distributed compilation support","Code signing and provisioning profiles must be pre-configured on the host — cannot be injected via MCP parameters","Build logs are captured as plain text — no structured parsing of compiler warnings/errors into machine-readable format","Coverage collection adds overhead to test execution — may slow tests by 10-20%","Coverage data is only available for code compiled with coverage instrumentation — requires rebuild","Coverage reports are limited to line/branch coverage — no path or mutation coverage","Performance profiling adds overhead to app execution — may affect measured metrics","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.6,"ecosystem":0.49999999999999994,"match_graph":0.25,"freshness":0.52,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-06-17T09:51:04.690Z","last_scraped_at":"2026-05-03T14:00:15.503Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=xcodebuildmcp","compare_url":"https://unfragile.ai/compare?artifact=xcodebuildmcp"}},"signature":"kbYYzhe34gamGXAx0vBgg9O/3LYJm3HaxhBDctP1hysPgcLkW9wR6FqCXHPdJ5xuQ/7rUt8lujv052iWHzUQBQ==","signedAt":"2026-06-22T05:34:36.981Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/xcodebuildmcp","artifact":"https://unfragile.ai/xcodebuildmcp","verify":"https://unfragile.ai/api/v1/verify?slug=xcodebuildmcp","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}