The MCP DigitalOcean integration is an open-source project that provides cloud resource management and operation interfaces based on the DigitalOcean API, supporting operations on various resources and tools.

The DS Core MCP Server project is a medical data integration toolset based on the DS Core Open API platform, including four independent MCP servers for patient management, document management, DICOM image management, and digital impression management, enabling large language models to securely and conveniently access medical data and services.

Loominus MCP is a visual node editor designed to simplify the configuration and sharing of Model Context Protocol (MCP) servers and agents. It connects MCP tools with LLMs through a drag-and-drop interface, supports the rapid construction of automated workflows, and is suitable for the development of intelligent tools in the digital and physical worlds.

EVDI is an end - to - end verifiable data infrastructure that provides digital identity and credential management for the AI agent ecosystem. It enables the authentication and trust establishment of AI agents through the Self - Sovereign Identity (SSI) model. The MCP Server, as an adapter for the SSI issuance service, exposes SSI operations as tools that can be called by AI models, supporting credential management and verification functions.

The DigitalOcean Database MCP Server is a middleware that connects AI development environments to DigitalOcean - hosted databases. It enables automatic discovery and connection to database clusters via API tokens, supports PostgreSQL and MySQL, and is compatible with multiple AI development tools.

The Tavus MCP server is an AI video generation service interface based on the Model Context Protocol, providing all functions of the Tavus API v2, including 25 tools such as AI digital human creation, video generation, conversational AI, lip-syncing, and speech synthesis.

MiniMe-MCP is an upgraded project for an AI development assistant. By creating a digital twin of the developer, it enables persistent memory and intelligent pattern recognition across projects. It solves the problem that traditional AI assistants lack memory and context understanding, provides personalized coding suggestions based on historical experience, supports multiple IDE tools, and can run locally to ensure data privacy.

The REAPER MCP Server is a project that exposes the functions of the REAPER Digital Audio Workstation through an API interface. It uses a Lua - Python hybrid architecture, supports file or socket communication methods, and provides 756 tools covering multiple areas of audio processing.