# AI interaction

A message context protocol server integrating Apache Kafka, providing publishing and consuming functions for LLM and agent applications.

A basic MCP server for AI clients to interact with etcd

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.

The GeoServer MCP Server is a server - side implementation of the Model Context Protocol (MCP) that connects large language models (LLMs) with the GeoServer REST API, enabling AI assistants to interact with geospatial data and services.

Android-MCP is a lightweight open-source project that serves as a bridge between AI agents and Android devices. It enables real-world task operations such as app navigation, UI interaction, and automated testing through the MCP server, without relying on traditional computer vision or pre-set scripts.

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.

An MCP server that provides browser automation capabilities for AI models, enabling models such as Claude and Gemini to perform web browsing, searching, and interaction operations through natural language instructions.

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.

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.

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.

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.

This project demonstrates how to set up a remote MCP server on Cloudflare Workers, including the entire process of local development, OAuth login, connection with MCP Inspector and Claude Desktop client, and deployment to Cloudflare.

The MySQL MCP Server is a model context protocol server designed for MySQL databases, enabling the interaction between AI models and MySQL databases through a structured interface.

This project is a Python server that connects the Claude desktop application and Unreal Engine 5.3, enabling the creation and editing of 3D scenes through text instructions. It supports functions such as basic object generation, blueprint invocation, and scene operation.

Frida MCP is an MCP protocol implementation based on the Frida dynamic detection toolkit, providing AI systems with the ability to interact with mobile and desktop applications.

This is an MCP server plugin developed for Autodesk Fusion 360, enabling AI assistants to directly interact with Fusion 360 through the MCP protocol, achieving functions such as design information acquisition, element modification, and CAD task prompting.

MCP Jenkins is an open-source project that bridges Jenkins with AI language models, follows Anthropic's MCP specification, and supports secure and context-aware AI interactions.

A Model Context Protocol (MCP) server implemented for Microsoft OneNote, providing a standardized interface for AI language models to interact with OneNote and supporting management functions for notebooks, sections, and pages.

An implementation of the Model Context Protocol (MCP) in Java and the Spring framework, providing a standardized interface for interacting with AI models and supporting synchronous/asynchronous communication modes.

BrowserTools MCP is a powerful browser monitoring and interaction tool that enables AI applications to capture and analyze browser data through Chrome extensions and a local Node server, and is compatible with multiple MCP clients.

An MCP server based on Playwright, providing browser automation capabilities for LLMs

Mobi MCP Server is a service based on the Model Context Protocol, used to enable the interaction between AI models and the Mobi knowledge management platform, providing functions such as search, data retrieval, content creation, and version control.

MacPilot CLI is an open-source tool that allows large language models to interact with the macOS system through the MCP protocol, providing system operation functions.

A curated list of Model Context Protocol (MCP) servers in the DevOps field, covering categories such as infrastructure as code, container orchestration, CI/CD, monitoring and observability, security, and other practical tools.

MCPvil is a minimized Wayland compositor based on the smallvil branch of the Smithay project. It integrates an MCP server, allowing AI agents and other MCP clients to interact with the compositor through stdio, providing functions such as application launch, screen capture, and mouse and keyboard simulation.

This project demonstrates how to set up a remote MCP server on Cloudflare Workers, including OAuth login functionality, supporting local development and cloud deployment, and enabling integration with the MCP inspector and the Claude desktop application.

A project that implements Server-Sent Events (SSE) based on the FastAPI framework, integrating the Model Context Protocol (MCP) function and providing a standardized interface for AI models to interact with external tools.

KognitiveKompanion is a modern and multi-functional AI interaction interface that supports desktop environments such as KDE and provides seamless integration with OpenAI, Ollama, and AMD Ryzen AI hardware acceleration.

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.