# AI interaction

A server-side project that implements the Model Context Protocol (MCP), supporting AI assistants to interact with external services and data sources, and providing functions for task creation, running, and debugging

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 MCP Inspector, and integration into the Claude desktop application for using mathematical tools.

mcp-chat is an open-source and general-purpose MCP client tool for testing and evaluating MCP servers and proxies. It supports command-line interaction and web mode, can connect to various MCP servers (JS/Python/Docker), and provides functions such as chat history recording, model selection, and system prompt customization to help developers debug MCP services.

A basic MCP server for AI clients to interact with etcd

A simple example of an MCP server that provides addition, greeting, and code analysis functions to help beginners learn the MCP protocol

This project is a Python-based multi-MCP server management framework that interacts with the Google Gemini API through the SSE protocol. It includes two major function modules: calendar management and browser automation, and supports dynamically loading multiple services through a configuration file.

This project demonstrates how to deploy a remote MCP server on Cloudflare Workers and implement OAuth login functionality. It provides a complete process guide for local development, MCP inspector connection, Claude desktop application integration, and cloud deployment.

The Tinderbox MCP Server is a service that enables AI assistants (such as Claude) to interact with the Tinderbox knowledge management application through the Model Context Protocol (MCP), supporting the operation of Tinderbox documents using natural language, including creating notes, updating attributes, and linking notes.

This project demonstrates how to set up a remote MCP server on Cloudflare Workers and implement OAuth login functionality. It provides a complete process for local development, MCP Inspector connection, Claude desktop application integration, and deployment to Cloudflare.

SwiftMCP is a Model Context Protocol (MCP) project implemented in Swift, including server and client components, used for the interaction between AI agents and Swift applications.

A server implementing the MCP protocol for the interaction between AI assistants and the Outline document service

The Dev Proxy MCP Server is a tool that provides Model Context Protocol (MCP) services for Dev Proxy, allowing AI assistants to interact with Dev Proxy functions through the MCP standard, including creating configurations, getting help, and discovering features.

The Unity MCP Server is a C# - based Model Context Protocol (MCP) service used to connect the Unity editor with external large - language models (LLM) or cloud - based AI agents to achieve real - time automation and intelligent interaction.

A model context protocol server that implements Jira integration, providing a standardized interface for AI models to interact with Jira, including REST API integration, connection pool, error handling and other functions.

The MCP startup project is an AI application development framework that includes a Python server - side and a TypeScript client - side, supporting the interaction between AI models and external tools/APIs, and providing functions such as document search and conversation management.

BrowserTools MCP is a powerful browser monitoring and interaction tool that enables in-depth interaction between AI and the browser through a Chrome extension and a local Node server. It supports multi-dimensional audits such as performance, SEO, and accessibility and is compatible with multiple MCP clients.

This is a Shopify MCP server project that enables interaction between AI agents and Shopify stores through a standardized protocol, providing functions such as API integration, product management tools, and store data access.

The MCP client project is used for advanced interaction with AI models and services, supporting tool calls and server management.

A lightweight file system service built on Python and the MCP library that securely exposes the file content and metadata in pre - configured directories and integrates with Claude AI for natural language interaction.

The A2A MCP Server is a service that bridges the Model Context Protocol (MCP) and the Agent - to - Agent Protocol (A2A), enabling MCP - compatible AI assistants (such as Claude) to seamlessly interact with A2A agents.

The n8n MCP Server is a protocol service that allows AI assistants to interact with n8n workflows through natural language, providing functions such as workflow management and execution monitoring.

Arcanna MCP Server is a service that interacts with Arcanna AI use cases through the Model Context Protocol (MCP), providing functions such as resource management, Python coding, event query, task management, feedback system, and health monitoring.

The AIStor MCP server is a service based on the Model Context Protocol (MCP) for interacting with AIStor object storage, supporting multiple operations including read - write, delete, management, and AI functions.

A Python-based MCP client and server example project, including a weather server implementation and a Claude AI interaction client. It requires an Anthropic API key to run.

GCP MCP is a service protocol that allows AI assistants to manage Google Cloud Platform resources through natural language interaction

The MySQL MCP Server is a MySQL database operation service based on the MCP protocol, providing a toolset for AI models to interact with MySQL, supporting Docker deployment and various database operation functions.

The multi-cluster MCP server provides a gateway for generative AI systems to interact with multiple Kubernetes clusters, supporting resource operations, cluster management, and monitoring.

Bonsai-mcp is a Blender plugin that enables analysis and operation of IFC building models through IfcOpenShell, supporting interaction with LLMs like Claude to perform building information model query tasks.

This project provides an MCP service for AI assistants to interact with the Mealie recipe database, supporting access through clients such as Claude Desktop.

A minimal server/client application implementation based on the Model Context Protocol (MCP) and Azure OpenAI, including the FastMCP server, Playwright testing framework, and MCP-LLM Bridge conversion function.