hyper-mcp is a high-performance MCP server based on WebAssembly plugins, supporting plugin distribution through container registries and suitable for various AI application scenarios.

FortunaMCP is a high-performance random number generation server based on hardware entropy, providing real and unpredictable random values for AI applications through various statistical distribution models, suitable for simulation and gaming scenarios.

The MCP portal is the official community platform for the Model Context Protocol, providing resources such as documentation, practical guides, server implementations, and tool integrations. It supports AI models to access external tools through the MCP protocol, covering a wide range of scenarios from database connections to multimodal applications.

FortunaMCP is an advanced MCP server that focuses on generating high-quality random values, suitable for scenarios such as simulation, modeling, and game mechanics in AI applications.

The Optuna MCP Server is a service based on the Model Context Protocol (MCP) that automates the optimization and analysis process using Optuna. It supports various application scenarios, such as automatic hyperparameter optimization for LLMs, interactive analysis of optimization results through a chat interface, and optimization of the input and output of other MCP tools.

This project provides a series of example modules using the AWS Model Context Protocol (MCP), covering multiple languages and technology stacks, including TypeScript, Python, Spring AI, etc., demonstrating the application of MCP in scenarios such as client-server communication, ECS deployment, and RAG integration.

Solon-AI is a Java AI application development framework for all scenarios, supporting multiple AI capabilities and can be embedded in various frameworks for use.

This project aims to enhance the versatility of AI agents, enabling them to adapt to a wider range of application scenarios.

The E2B Cookbook is a project containing various example codes and guides for development using the E2B SDK. It covers a variety of scenarios from basic introduction to advanced applications, including integration with different LLM providers, integration of AI frameworks, and practical application cases.

An MCP server designed for Claude Desktop that can obtain transcripts via YouTube video URLs, expanding the application scenarios of LLM functions.

Implement intelligent applications in sales scenarios through the MCP server, suitable for various AI chat environments

An e - commerce demonstration application based on the Model Context Protocol (MCP), built with Next.js and TypeScript, integrating the FakeStore API, demonstrating the application of MCP in e - commerce scenarios.

This project demonstrates how to deploy a remote MCP server on Cloudflare Workers and implement the OAuth login function. It supports local development and debugging, connection testing through the MCP Inspector, and scenarios such as integrating the Claude desktop application to call mathematical tools. Finally, it can be deployed to the Cloudflare cloud service.

The official website of A2A-MCP showcases the technical vision, core advantages, and application scenarios of the multi-agent collaboration protocol, and is built using a modern front-end technology stack.

The Chatvolt MCP Server is a TypeScript-based application designed to extend the capabilities of AI agents by providing a set of tools to enable them to interact with the Chatvolt platform. This project serves as a bridge between AI models and the Chatvolt API, supporting operations such as managing agents, querying data storage, and handling CRM scenarios, thereby automating complex workflows and providing a natural language interface for the Chatvolt platform.

AWorld is a multi - agent system framework aiming to bridge the gap between theoretical MAS capabilities and practical applications, providing a full - set solution from single - agent to multi - agent collaboration/competition. The project supports scenarios such as browser/mobile operations and GAIA benchmark testing, adopts a client - server architecture, integrates a rich toolchain, and includes performance evaluation and training functions.

The Gemini MCP Server is a single executable file developed in Go, integrating the Model Control Protocol server of Google Gemini API. It provides dynamic model access, advanced context caching, intelligent file handling, and enhanced search functions, supporting various application scenarios such as code analysis, creative writing, and factual research.

mcp - agent is a lightweight AI agent framework based on the Model Context Protocol (MCP), which supports building efficient agent applications through a simple and composable model. It integrates the lifecycle management of the MCP server and implements multiple workflow models, such as parallel processing, routing, evaluation optimization, etc., and is suitable for various AI application scenarios such as multi - agent collaboration and human - machine interaction.