MacPilot CLI is an open-source tool that enables large language models to interact with the macOS system through the MCP protocol, providing system operation functions.

MacPilot CLI is an open-source tool that allows large language models to interact with the macOS system through the MCP protocol, providing system operation functions.

The Model Context Protocol (MCP) is an open-source protocol that provides a series of reference implementations and community-built servers, enabling large language models (LLMs) to access tools and data sources securely and controllably. The project includes implementations of various functional servers, covering areas such as file systems, databases, search, and API integration, and supports development with TypeScript and Python SDKs.

The Model Context Protocol (MCP) is an open-source protocol designed to enable Large Language Models (LLMs) to seamlessly interact with external tools, services, and data sources through a standardized interface, simplifying the integration process and expanding AI capabilities.

The Model Context Protocol (MCP) is an open-source protocol that provides a series of reference implementations and community-built servers, enabling large language models (LLMs) to access tools and data sources securely and controllably. This project includes various types of server implementations, covering multiple domains such as file systems, databases, Git, and Slack, and supports TypeScript and Python SDKs.

MCP-OpenLLM is a LangChain wrapper for seamless integration of different MCP servers and open-source large language models (LLMs), supporting the use of LangChain community models.

A RAG system built with open-source embedding models, vector databases, and the Gemini large language model, supporting local document processing and dynamic index update.

One API is an open-source project that provides a unified access interface to various large models through the standard OpenAI API format. It supports multiple large models and third-party proxy services, and has functions such as load balancing, token management, and user grouping. It is suitable for various deployment scenarios.

Model Context Protocol (MCP) is an open-source protocol that provides a series of reference implementations and community-developed servers, enabling large language models (LLMs) to securely and controllably access tools and data sources. The project includes various types of server implementations covering multiple domains such as file systems, databases, Git, and Slack, demonstrating the diversity and scalability of MCP.