"A management control platform (MCP) compatible with the Cypress framework" matching MCP servers:

A lightweight and modular framework for building MCP-based file management systems with standardized module structure, flexible configuration, and extensible functionality registration mechanisms.

Provides full control of a macOS system, enabling AI agents to execute shell commands, run AppleScript, manage files and processes, and perform human-like GUI interactions such as clicking, dragging, scrolling, and typing, with a screenshot-based perception loop.

Turns Canvas LMS into a scriptable pipeline and exposes it to AI assistants via MCP for querying courses, grades, assignments, and syncing files using natural language.

Provides tools for file system operations and text generation using OpenAI-compatible models via the Model Context Protocol, supporting both stdio and HTTP transports.

Enables comprehensive Android device control over ADB, including UI automation, screen capture/recording, app management, file operations, and log/notification access, with a built-in permission system.

Enables AI agents to remotely operate visual design tools via MCP protocol, with composable architecture for image processing, file operations, and workflow automation.

A local MCP bridge that lets ChatGPT chat mode operate the user's own computer, running project, file, and shell tasks through a local executor and returning progress and results to the conversation. It also coordinates Codex sessions (persistent or one-off) and other agent CLIs as sub-agents.

Enables ChatGPT web to read local files, search code, run shell commands, and drive a local Codex CLI via an official MCP connector, with human approval for risky commands and full audit logging.

Five generic MCP tools for deep Home Assistant administration, plus a native Home Assistant LLM API and a reusable agent skill.

A safety-first MCP server enabling file inspection/editing, allowlisted command execution, process listing, and optional desktop automation. It emphasizes security with disabled writes/commands/GUI by default and local feature gates.

A production-grade MCP server that lets AI cloud services control and manage your Linux server securely via HTTP/SSE.

Manage local/SSH/WinRM remote hosts via MCP, providing tools for exec, filesystem, screen, process, serial console, and configuration.

A general-purpose MCP server that provides utility tools for echo, date/time, and file operations within Claude Code and Claude Desktop. It functions as an extensible framework designed to help developers easily build and register custom Python-based tools.

Enables comprehensive filesystem operations across Linux, macOS, and Windows with platform-aware command execution, secure path restrictions, and intelligent adaptations for file search, directory management, and shell commands specific to each operating system.

Enables users to directly edit authoritative Markdown context and tables within Codex, review the complete text before saving, and commit tracked immutable revisions with version history.

Enables integration between Claude AI and Nasuni environments to monitor appliance health, manage volumes and shares, and generate comprehensive infrastructure reports. Users can interact with the Nasuni Management Center through natural language to track performance metrics and summarize system notifications.

Provides a sandboxed filesystem API for AI agents, enabling natural-language file read, write, append, delete, move, list, create, and metadata operations through MCP tools.

Enables Claude to create, edit, run, and manage reusable skills stored locally, including executing scripts with automatic dependency management and environment variables. Works across all MCP-compatible clients like Cursor, Claude Desktop, and claude.ai.

Provides comprehensive PC control capabilities including file operations (read, write, edit, delete), directory management, file search, and shell command execution through the Model Context Protocol.

An MCP server that converts Markdown files containing Mermaid diagrams into PDF documents by rendering diagrams as SVG images. It provides a specialized tool to automate document conversion while ensuring all visual charts are correctly embedded in the final output.