# Vector storage

mcp-rag-server is a service based on the Model Context Protocol (MCP) that supports Retrieval Augmented Generation (RAG) and can index documents and provide relevant context for large language models.

The Shared Knowledge MCP Server is a middleware that provides unified knowledge base services for multiple AI assistants, enabling efficient information retrieval and sharing through RAG technology.

An MCP server project based on the Spring AI framework, using the Sync SSE transmission protocol, integrating the AWS Bedrock service, and utilizing PostgreSQL for vector storage.

Metis MCP Tools is a repository containing multiple toolkits, aiming to enhance the functions of Metis RAG applications. These tools provide functions such as database management, vector storage operations, document processing, and LLM interaction, and enable language models to interact with external resources through the standardized Model Context Protocol (MCP).