Genkit is an open-source framework for building AI-driven applications, providing Node.js and Go libraries, supporting the integration of multiple AI models and vector databases, and including development tools and a plugin ecosystem.

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.

LOTUS-MCP is an open-source model coordination protocol that integrates the two major AI models, Mistral and Gemini, providing a unified interface, context sharing, and tool integration to achieve intelligent routing and cost optimization.

OpenManus is an open-source project that allows users to realize various ideas without an invitation code. It was built by members of the MetaGPT team in 3 hours. It provides a simple implementation that allows users to create their own intelligent agents and supports multiple languages and configurations. The project welcomes suggestions, contributions, and feedback. Future plans include better planning, real-time demonstrations, playback functions, RL fine-tuning models, and comprehensive benchmarking.

A TypeScript bridge project connecting local LLMs to MCP servers, providing a web interface that enables open-source models to use tool capabilities similar to Claude, supporting functions such as file system operations, web search, and complex reasoning.

SolidPilot is an open-source SolidWorks AI assistant that uses a modular architecture to interact with local language models (such as Claude) through the MCP protocol, including technical components like the Python layer, C# adapter layer, and COM bridge.

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.

MCP Jenkins is an open-source project that bridges Jenkins with AI language models, follows Anthropic's MCP specification, and supports secure and context-aware AI interactions.

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.

Easy-MCP-Use is an open-source TypeScript library designed to connect any LLM to any MCP server and build custom agents with tool access rights. It supports multiple LLM models and MCP servers, providing functions such as dynamic server selection, multi-server support, and tool restrictions, enabling developers to easily connect LLMs to various tools.