# Automation

This project is a Todoist server application based on the Model Context Protocol, allowing users to interact with Todoist through an LLM (such as Claude) and supporting all Todoist API features.

The Computer Use AI SDK developed by Screenpipe is an open - source project that provides an MCP server and client for controlling computer operations through AI. It supports the native macOS environment, does not require a virtual machine, can directly interact with any application or website, and provides basic functions such as launching applications, reading content, clicking, and entering text, aiming to build automated workflows and intelligent agents.

A service that opens a browser and accesses a specified website

Unity MCP is an AI assistant tool that controls the Unity editor through natural language commands. It supports creating, modifying, and managing game objects, scenes, materials, etc., and simplifies the development process.

The Chatvolt MCP Server is a TypeScript-based application designed to extend the capabilities of AI agents by providing a set of tools to enable them to interact with the Chatvolt platform. This project serves as a bridge between AI models and the Chatvolt API, supporting operations such as managing agents, querying data storage, and handling CRM scenarios, thereby automating complex workflows and providing a natural language interface for the Chatvolt platform.

A web page screenshot service based on Puppeteer

X_MCP is a server project for automatically publishing content on the X platform (formerly Twitter).

The Alibaba Cloud Operation and Maintenance MCP Server project provides a variety of cloud product operation tools, including functions such as starting, stopping, and querying services like ECS, VPC, RDS, and OSS, and supports automated operation and maintenance through API and OOS.

MCP Servers Schemas is a project that provides various MCP server definitions. Users can quickly obtain the latest server information and tool definitions without local installation.

Yingdao RPA MCP Server is an implementation based on the Model Context Protocol (MCP), providing a service for Yingdao AI Power and other MCP Host tools to call RPA capabilities. It supports the local mode and the open API mode, and can query and run RPA applications, upload files, manage jobs, etc.

An MCP server based on the WordPress REST API, providing functions such as creating, retrieving, and updating posts, enabling programmatic interaction between AI assistants and WordPress sites.

The Claude Kubernetes MCP server is a Go-based integrated platform that combines ArgoCD, GitLab, and Claude AI to achieve advanced control and automation of the Kubernetes environment.

The Edge Delta MCP Server is a server based on the Model Context Protocol, used for seamless integration with the Edge Delta API, enabling developers to build automation tools and AI applications to analyze observational data.

An email sending MCP server based on the Resend API, allowing LLMs to write and send emails.

Tencent Cloud COS MCP Server is a service that allows large models to quickly access Tencent Cloud Storage (COS) and CI capabilities without coding, providing cloud storage and processing functions such as file upload and download, image processing, and video processing.

A SearXNG search integration MCP server designed for n8n workflows, supporting the configuration of search requests via JSON parameters.

AutoMCP is a tool that automatically generates server and client code compatible with the MCP protocol based on YAML service definitions, supporting the rapid implementation of tool functions and the organization of service code.

An MCP server that enables LLM to interact with network devices via SSH (netmiko)

An MCP server built on FastMCP that exposes the SQLMap CLI tool as MCP functions for automated SQL injection testing and database reconnaissance.

XcodeMCP is an MCP server and CLI tool that controls Xcode through JavaScript automation, providing functions such as project building, testing, debugging, and XCResult analysis.

This is an MCP server project that enables direct search and retrieval of SAP Notes/KB article content through SAP Passport certificate authentication and Playwright automated browser technology.

Changesets is a build tool for managing versions and releases in multi - package or single - package codebases, providing automated generation and documentation support.

The Codex MCP Tool is an open-source MCP server that connects the IDE or AI assistant to the Codex CLI, supporting non-interactive automation, secure sandbox editing, and large-scale code analysis. It provides progress streaming updates and a structured change mode.

This is a tool that provides a complete MCP server for RPG Maker MZ game development, supporting the automatic generation of game projects, maps, events, database content, and game assets through MCP tools and AI (Gemini), enabling programming - based or AI - driven game development without a GUI.

The Claude Kubernetes MCP Server is a Go - based integrated platform that combines ArgoCD, GitLab, and Claude AI to achieve advanced automated control of Kubernetes environments.

This project automatically collects arXiv papers through the arxiv_mcp_project and uses AI to generate quick summaries, aiming to help users efficiently obtain the core content of papers.

An OmniFocus integration service designed for Claude Desktop, providing task management functions through the MCP protocol, supporting task and project retrieval and intelligent filtering

The Flutter MCP Server is an open - source implementation of the Model Context Protocol (MCP) for the Dart/Flutter ecosystem. It provides a unified API interface for AI assistants and developer tools, supports remote calls to the Dart/Flutter development toolchain, and enables secure and programmable automated development processes.

The Logseq MCP Server is a model context protocol server that provides direct integration with Logseq knowledge bases, enabling LLMs to interact programmatically with Logseq graphs.

This project demonstrates the training of a linear regression model using Claude and the Model Context Protocol (MCP) for an end-to-end machine learning workflow. Users only need to upload a CSV dataset, and the system can automatically complete the entire process of data preprocessing, model training, and evaluation (RMSE calculation).