"Information about Xcode development environment" matching MCP servers:

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

MCP server for managing Xcode Cloud workflows, builds, and test artifacts via the App Store Connect API.

Local MCP server enabling agents to track Xcode Cloud builds and access TestFlight crash reports through the App Store Connect API.

MCP server for Xcode build optimization, providing build-timing analysis, DerivedData/module-cache management, and build-speed config linting for AI coding agents.

A unified control center for managing MCP servers, providing tooling for environment variable management, profile-based configurations, and local package installation automation.

Provides secure access to containerized build environments for software projects, enabling AI assistants to execute builds, run tests, manage git operations, and inspect build artifacts without requiring local installation of dependencies.

An MCP server that enables AI-powered IDEs to implement a structured development workflow from requirements gathering to code implementation, guiding users through goal collection, requirements specification, design documentation, task planning, and execution.

An MCP server that enforces development discipline and workflow best practices, guiding users through a structured process of coding, testing, documenting, committing, and releasing.

Provides structured access to Xcode development tools including xcrun, xcodebuild, and xctrace for building, testing, and analyzing projects.

A Model Context Protocol server that allows management of Netlify sites, enabling users to create, list, get information about, and delete Netlify sites directly from an MCP-enabled environment.

SSWP MCP — Deterministic software attestation for AI-augmented development. Witness any repo through a 5-gate pipeline, adversarially probe dependencies, and produce self-verifying .sswp.json attestations. Fleet registry across 131 nodes with tamper-proof audit ledger and FTS5 search. Agent-native — one tool call from Hermes, Claude, or Cline.

Deploys and manages projects on Swigs Cloud from any MCP client, turning folders or git repositories into live HTTPS sites in about two minutes.

Enables AI agents to deploy, manage, and configure web applications on sota.io, including project creation, deployment, environment variables, custom domains, and rollbacks.

An MCP server that provides deterministic tools for AI assistants to standardize development workflows, including branch naming, commit validation, and PR checklists.

Aegis keeps Claude Code, Codex CLI and Antigravity on your project's rules via a zero-dependency Model Context Protocol (MCP) server (aegis-mcp), AGENTS.md / CLAUDE.md bootstrap, git pre-commit hooks, and CI governance (aegis check). It serves each agent just-in-time rules for the files it is about to edit, then enforces AST and repository invariants before commit and in pull requests.

Enables Claude to run structured software development pipelines by directing it through sequential phases, validating evidence before advancing, and persisting state in SQLite for resumption across sessions.

Enables AI assistants to deploy and manage SnapDeploy containers and resources—including builds, logs, environment variables, databases, and custom domains—directly through natural language.

Enables AI assistants to deploy, manage, and rollback websites via the Krexel API, supporting site uploads, deploys, logs, rollbacks, environment variables, and status checks.

An MCP server designed for React Native and Expo development that provides specialized tools for project scaffolding, architectural best practices, and troubleshooting. It enables AI assistants to guide users through setup, navigation configuration, and CI/CD processes using modern stacks like NativeWind and Zustand.

An MCP server providing comprehensive Gitea API coverage with 186 tools for managing repositories, issues, pull requests, and CI/CD workflows. It enables autonomous AI agents to perform complex development and administrative tasks directly through a Gitea instance.

Turns JUnit XML test reports from CI into queryable QA metrics, letting AI assistants answer plain-English questions about failures, flaky tests, regressions pinned to a commit, root-cause clusters, and performance drift. Also generates ready-to-share QA health reports and self-contained HTML dashboards without logging into separate tools.

Enables management of Railway.app infrastructure through natural language, including deploying services from GitHub repos or Docker images, managing environment variables, monitoring deployments, and configuring networking and volumes.

A Model Context Protocol server that lets development agents work with Odoo.sh from their development environment, listing branches, watching builds, and streaming logs. It sits on top of the odouche Python library's public interface.

Enables coding agents to build, test, archive, and run iOS apps on a remote Mac fleet from any environment, with XcodeBuildMCP-compatible tools and live simulator access.

A Model Context Protocol (MCP) server for LocalStack that enables management of local AWS development environments, including container lifecycle operations, infrastructure deployments, log analysis with IAM policy generation, chaos injection, and Cloud Pods state management.

Enables management of Railway.app infrastructure through natural language, including deploying services, managing environment variables, monitoring deployments, and handling databases and volumes.

Enables AI coding agents to orchestrate the full software development lifecycle on GitHub, including planning, issue creation, code review, security triage, and release readiness checks.

Enables management of Railway.app infrastructure through natural language, allowing users to deploy services, manage environment variables, monitor deployments, and configure projects directly from MCP clients like Claude.

Enables AI agents to manage self-hosted Coolify v4 instances, including listing applications, safely handling environment variables with masking and dry runs, deploying, restarting, and reading logs.

Enables management of Railway.app infrastructure through natural language, including deploying services, managing environment variables, monitoring deployments, and controlling project resources.