This project includes two servers based on the Model Context Protocol (MCP): an IoT device control server and a memory management server. The IoT server provides device control, status query, and real-time update functions, suitable for scenarios such as smart homes and industrial IoT; the memory management server provides long-term memory storage and semantic search functions, suitable for fields such as conversation history and knowledge management.

An MCP server that supports voice interaction with LLMs such as Claude. You only need an OpenAI API key and a microphone/speaker to have a real-time voice conversation.

A lightweight bridge service that enables Claude AI to search the web in real-time. This project is based on a Flask server, integrating Claude's advanced capabilities and DuckDuckGo search, allowing the AI to obtain real-time information during conversations.

A modern MCP server implementation that supports multi-AI providers, real-time response, conversation management, and monitoring functions, using a microservices architecture.

MCP Telemetry is a server based on the Model Context Protocol for conversation tracking and data analysis in a chat system through Weights & Biases Weave. It provides functions such as session tracking, LLM interaction recording, and tool call monitoring, and supports real-time visualization and analysis.

The official TestingBot MCP server enables AI assistants to manage the TestingBot testing infrastructure through a conversational interface, including functions such as real-time testing, browser and device management, test management, storage management, screenshot testing, build management, user team management, CDP sessions, and tunnel management.