# Protocol Integration

The Quickchat AI MCP Server is a tool that allows users to integrate the Quickchat AI agent into various AI applications, supporting seamless connection through the Model Context Protocol (MCP). Users can quickly deploy and use their Quickchat AI agents in applications such as Claude Desktop and Cursor through simple configuration.

MCP is an AI chat system based on a client-server architecture that supports extending the capabilities of Claude AI through multiple dedicated servers (file system, Slack, Brave Search), enabling it to access local files, Slack workspaces, and real-time web information.

The MCP plugin of ElizaOS implements the integration with the Model Context Protocol (MCP), enabling agents to connect to multiple MCP servers and obtain resource, prompt, and tool support.

An AI infrastructure-as-code platform based on Model Context Protocol (MCP), integrating Ollama for intelligent agent programming and server management.

The MCP Search Server is a protocol service that provides Google search functionality for AI models. It supports caching and advanced search configurations and enables information retrieval through Docker deployment.

This project demonstrates how to deploy a remote MCP server on Cloudflare Workers and implement OAuth login functionality. It supports local development and debugging, connection and testing through the MCP Inspector, integration with the Claude desktop application, and finally can be deployed to the Cloudflare cloud for remote calls.

PrivateGPT MCP Server is a server implementation based on the Model Context Protocol (MCP) for integrating PrivateGPT as a proxy into MCP - compatible applications. It supports interacting with the PrivateGPT API through the MCP protocol, including functions such as chatting, knowledge source management, and group permission control, and provides powerful security features such as TLS encryption, RSA password encryption, and key management.

This project demonstrates how to deploy a remote MCP server on Cloudflare Workers and implement OAuth login functionality, supporting connection and use through the MCP inspector and the Claude desktop application.

This project demonstrates how to deploy a remote MCP server on Cloudflare Workers, including the entire process of local development, MCP inspector connection, Claude desktop application integration, and cloud deployment.

This project demonstrates how to deploy a remote MCP server on Cloudflare Workers and implement OAuth login, supporting connection and use via the MCP checker and Claude desktop client.

Nautobot MCP is a Nautobot plugin that integrates the MCP protocol server, providing an AI tool interface for network automation and management.

A project that provides an MCP protocol server for PipeCD, supporting integrated management of applications and deployments.

This project demonstrates how to integrate Claude AI into the development process through the MCP protocol, including an MCP server and a to-do application demonstration to achieve AI-assisted software development.

This project demonstrates how to set up a remote MCP server on Cloudflare Workers and implement the OAuth login function. It supports local development and debugging, connection and testing through the MCP inspector, integration with the Claude desktop client, and final deployment to Cloudflare cloud services.

SketchupMCP is a project that connects Sketchup to Claude AI through the Model Context Protocol (MCP), enabling direct control of Sketchup by AI and interactive 3D modeling.

A server based on the Model Context Protocol (MCP) and Server-Sent Events (SSE), integrating the Brave Search API to provide real-time streaming search functionality for AI models and clients.

This project demonstrates how to deploy a remote MCP server on Cloudflare Workers and implement OAuth login functionality, supporting connection and use through the MCP checker and Claude desktop client.

A Claude desktop alternative application developed based on Tauri + React + TypeScript, supporting the MCP server protocol

This project demonstrates how to set up a remote MCP server on Cloudflare Workers and implement OAuth login. It supports local development and debugging, connection testing via the MCP inspector, integration with the Claude desktop client, and finally deployment to the Cloudflare cloud.

An integration toolkit for Wireshark and the MCP protocol, supporting interaction between natural language and network analysis, including a Python server and Lua extension components.

VeyraX MCP is a unified tool connection protocol that enables multi-environment tool integration through single authentication.

A curated list of Model Context Protocol (MCP) servers, optimized for AI assistants like Claude, providing services such as file access, database connection, and API integration to extend AI capabilities.

MCP Tools is a server project that implements the Model Context Protocol (MCP), providing file system and command execution tools for LLM clients such as Claude Desktop, and extending the local system interaction capabilities of large language models.

This project demonstrates how to deploy a remote MCP server on Cloudflare Workers and implement OAuth login functionality. It supports local development and debugging, connection testing via the MCP Inspector, and allows the Claude desktop client to call the MCP service.

Molecule-MCP is a server that connects molecular science tools with Claude AI, enabling AI to directly control molecular modeling tools through the MCP protocol

MCP Servers is a platform dedicated to showcasing and connecting Model Context Protocol (MCP) servers, providing developers with convenient MCP server discovery and integration services.

An integrated service that provides MCP protocol support for PipeCD

An MCP protocol server based on standard input and output, providing access to Gravatar avatars and personal profile data, supporting information query through email or hash.

Awesome MCP Servers is a curated list of Model Context Protocol (MCP) servers, covering multiple categories such as file systems, databases, web search, version control, communication, and developer tools, aiming to expand the capabilities of AI models.

This guide introduces how to build an MCP server using Python, enabling AI assistants to interact with external tools and data sources through the MCP Python SDK, including installation, quick server setup examples, testing, and deployment considerations.