"How to control macOS settings or functions" matching MCP servers:

MCP server to manage and deploy Scaleway Serverless Functions, enabling creation, listing, updating, deleting, downloading, and logging of functions through natural language.

An MCP server that adds engineering discipline to AI-assisted development, enforcing evidence-gated TDD, security review, backup strategy, and deployment generation to turn AI-generated code into production-ready software.

A demonstration project for building and running Model Context Protocol (MCP) servers using Netlify Serverless Functions. It provides a template for deploying serverless MCP endpoints with automated CI/CD pipelines through Netlify.

Converts Jenkins declarative pipelines into GitHub Actions workflow YAML files, facilitating migration from Jenkins to GitHub Actions CI/CD.

Provides secure, controlled access to GitHub operations through the Model Context Protocol with enterprise-grade security features including secret detection, vulnerability scanning, rate limiting, and full audit trails. Supports repository management, file operations, branch creation, commits, and GitHub Actions workflows.

Publishes static sites to Drop2Run from an AI agent: hand it files written in the chat or a folder on disk, and it returns a live HTTPS URL. Six tools — publish_files, publish_dir, list_sites, delete_site, and login / login_code — with no git, no build step and no repository.

Enables AI coding tools to validate local projects and publish or update applications to Bedengan App Hub via API, with automated checks and live deployment without manual approval.

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

Checks whether software dependencies (npm packages, GitHub Actions, MCP servers, Docker images) are alive, dormant, abandoned, archived, or deleted using dated observations from lastseen.dev.

An MCP server that drives the full App Store release cycle for iOS and macOS apps: version bump, archive + TestFlight upload, metadata, review submission, and status.

Enables agents and CI pipelines to audit MCP servers and agent tool-chains by statically scanning repositories, local checkouts, tools/list exports, or live endpoints for risks such as destructive actions without confirmation, mismatched safety annotations, injection surfaces, credential or PII exposure, and unguarded command, path, or URL sinks. All checks are read-only and never execute the scanned code or call tools/call.

Enables headless batchmode control of Unity projects for compile, test, build, and screenshot tasks, avoiding the need for an interactive editor.

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.

MCP server for agent-controlled deployment on Pier, exposing 14 tools mapped to Pier REST API endpoints for managing deployments via stdio or HTTP.

Enables AI assistants to manage and operate Venelx CI/CD pipelines through the Venelx REST API, including listing projects, triggering builds, checking status, tailing logs, accessing artifacts and workers, and diagnosing signing or GitHub access.

A local MCP server that exposes Blacksmith.sh's usage and cost data, enabling queries for CI spend through agents, alerts, or dashboards.

Governance/control plane for MCP-enabled coding-agent workflows with validation, findings, approvals, budgets, and proof bundles.

Deploys projects straight from an AI agent to Snaphost and returns a public URL, with automatic Dockerfile generation, build/run/log management, and deploy lifecycle control.

Self-hosted coding agent that runs Claude Code or Codex in your own infrastructure and works from Slack. Exposes codebase investigation, file edits, branch and PR creation, allowlisted command execution, CI status and an audit log as MCP tools, keeping every credential behind the tool layer instead of handing it to the model.

Connects AI assistants to GitHub Actions workflows to monitor CI/CD pipelines, view run logs, diagnose failures, and optionally trigger or manage workflows with granular permission controls.