# Model Protocol

This is a project demonstrating how to create and test an MCP (Model Context Protocol) server, including environment setup, server creation, addition of tools and resources, and testing via the MCP Inspector and Claude Desktop.

The SmallCloud MCP Server is a demonstration project based on the Anthropic model context protocol SDK for interacting with MCP hosts such as Claude Desktop. This project provides a demonstration version for Mac OS, includes a simple tool example, and supports integration with Claude Desktop through a configuration file.

An HTTP/SSE proxy server based on Node.js, used to simplify interaction with MCP (Model Context Protocol) services, providing HTTP interfaces and real-time event push functions.

Axe Handle is a reference project for an MCP server implemented in Golang, mainly used for learning and laying the foundation for subsequent work. Currently, it only supports basic communication with the Claude Desktop client.

The OpenRouter MCP Multimodal Server is a protocol server that provides text chat and image analysis functions through OpenRouter.ai, supporting multiple model selections and performance optimization.

3D-MCP is a general model context protocol implementation for 3D software, enabling LLMs to interact across platforms such as Blender, Maya, and Unreal through a unified TypeScript interface.

The Sufy MCP Server is a Model Context Protocol server based on Sufy products, allowing users to access various Sufy functions through this service in large AI model clients.

A well - organized collection of Model Context Protocol (MCP) servers, covering enterprise support implementation, demonstration implementation, integration tools, community contributions, and development frameworks, aiming to provide developers with rich resources and tools.

MCP Base is a general model context protocol framework for building AI-driven applications. It provides standardized server and client implementations, supporting multiple integrations and modular design.

The Higress AI-Search MCP Server provides real-time search engine result enhancement for AI models

MKP is a Model Context Protocol (MCP) server specifically designed for Kubernetes, providing tools for interacting with Kubernetes clusters and supporting resource query and application operations.

This project implements an MCP server that interacts with Autodesk platform service documentation, focusing on the Model Derivative API and supporting the invocation of Autodesk APIs through tools such as Cursor or Claude.

The Perplexity AI MCP Server project provides a standardized interface to access the features of Perplexity AI, including chatting, searching, and document retrieval.

oatpp-mcp is an implementation of Anthropic's Model Context Protocol (MCP) based on the Oat++ framework, supporting auto-generated API tools, STDIO and HTTP SSE transmission methods, as well as server functions such as prompts, resources, and tools.

This project is a proof-of-concept (POC) that demonstrates how to implement the Model Context Protocol (MCP) through a custom host for testing agentic systems. Core features include OpenAI-compatible API, Google Gemini integration, streaming response support, and tool invocation capabilities.

Glutamate MCP Servers is a project containing multiple MCP servers, supporting easy deployment and management via the Glutamate platform. The project provides custom servers such as UI Assist and supports all Node - based stdio and sse protocol servers.

CereBro.Unity is a model-agnostic AI agent wrapper based on CereBro, supporting the Model Context Protocol (MCP), allowing developers to write tools that can be used across AI models.

The MCP Server of the Flowcore platform is used to manage and interact with Flowcore resources, providing a standardized API interface.

AytchMCP is a model context protocol server for Aytch4K applications, supporting interactions with multiple large language models and including functions such as resource management, tool components, and protocol processing.

Model Context Protocol Service based on Epsilla

Revit MCP integration is a bridge connecting Autodesk Revit and AI assistants, enabling model interaction through natural language.

A JSON-based unified interface dbt Model Control Protocol (MCP) server that supports triggering dbt model runs and tests through the CLI, API, or AI tools and provides Slack notification functionality.