A Java class analysis service based on the MCP protocol. It scans Maven dependencies, decompiles Java class files, and provides detailed class information to help LLMs accurately generate code for calling second-party/third-party package interfaces, thus solving the problem of incorrect coding caused by AI's inability to read dependency source code.

The KubeBlocks Cloud MCP Server is a service based on the Model Context Protocol (MCP) that provides seamless integration with the KubeBlocks Cloud API, enabling AI assistants to manage cloud resources through standardized tools by calling interfaces.

A Godot 4 example project containing an MCP client plugin, used to demonstrate real-time viewing, modifying scene node attributes, and calling methods through AI tools such as Claude during game runtime, enabling AI-assisted debugging and development.

The Grok MCP plugin is an interface plugin that provides the powerful features of Grok AI for Cline, supporting text generation, image analysis, and function calling.

This project demonstrates the basic client-server interaction based on the Model Context Protocol (MCP), expanding the capabilities of AI models through an independent server and providing the function of calling computing tools.

A minimalist MCP server example based on Java and Spring Boot, which implements weather query functions by calling the Gaode Weather API and supports AI clients to obtain weather data through the MCP protocol.

The Gaia MCP Server is a server implementation based on the Model Context Protocol (MCP), supporting communication with large language models (LLMs) through stdio and SSE. It provides a standardized tool - calling interface and especially integrates AI image generation and processing functions.

Overview: The MCP server is an intermediate layer that informs the AI agent of the currently available services, APIs, and data sources. It enables the AI agent to decide whether to call a certain service based on the information provided by the Server and execute functions through Function Calling.

A server based on the Model Context Protocol that enables AI image generation functions by calling the Flux model through the Cloudflare Worker API, and is compatible with multiple AI assistant tools.