# Data Connection

This project demonstrates an example implementation of the Model Context Protocol (MCP), which is a standardized protocol for enhancing the capabilities of AI assistants and extending their functionality through custom tools and data sources. The project includes multiple MCP server examples, such as task managers, file explorers, and weather services, and provides guidelines on how to set up and use these servers.

mcp-get is a command-line tool used to discover, install, and manage MCP servers, simplifying the connection between LLMs and external data sources.

This project is an implementation of the Model Context Protocol (MCP) server, demonstrating how to build a functional server that can be integrated with multiple language model clients. As a standardized protocol, MCP provides a unified way for AI applications to connect data sources and tools, supporting three types of capabilities: resources, tools, and prompts.

An MCP server implementation for providing CData Connect Cloud data connection for the Claude desktop application

Awesome MCP Servers is a curated list of Model Context Protocol (MCP) servers and tools. MCP is an open standard introduced by Anthropic that enables AI models to connect to external data sources and tools through standardized interfaces, enhancing their capabilities.

This project is an example of an MCP server based on Spring Boot, implementing the Model Context Protocol standard. It allows developers to expose data through the MCP server or build AI applications that connect to these servers. In the example, a simple information service is created to provide developer information to the Claude desktop application through the MCP protocol.

MCP-Gateway is a service that provides unified management capabilities for MCP Server, helping AI agents quickly connect to various data sources, and supporting HTTP interface conversion, OpenAPI integration, and routing management.