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.

Claude Context is an MCP plugin that provides in - depth context of the entire codebase for AI programming assistants through semantic code search. It supports multiple embedding models and vector databases to achieve efficient code retrieval.

A memory system that enhances AI programming capabilities through multi-type database integration, including vector databases, SQLite, and knowledge graphs, for storing and retrieving code patterns, algorithms, and relationships between programming concepts.

A multi - agent AI infrastructure based on the Model Context Protocol (MCP), providing a standardized communication layer, supporting vector databases, tool integration, and multi - agent collaboration, including core components such as an inspector dashboard, Qdrant vector database, and Docker network.

A Python server project based on the MCP protocol, which uses OpenAI's vector storage function to build a RAG system, supporting the creation of vector databases from multiple file formats and semantic search.

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.