A bridge that connects physical hardware devices with AI large language models via serial communication, allowing users to control hardware using natural language commands.
Links IoT devices to AI large models using the MCP and MQTT protocols, enabling natural language control, real-time AI responses, and complex instruction execution for interconnected IoT devices.
An MCP server that bridges the physical world and AI models by enabling natural language control of IoT hardware via the MQTT protocol. It supports real-time device monitoring, command publishing, and response handling for seamless integration between AI clients and physical devices.
Bridges the Model Context Protocol (MCP) with ESP32 devices running Tasmota firmware, enabling LLMs to send structured commands like toggling relays or reading sensors via HTTP.
Enables cloud LLM agents to discover and invoke physical hardware on edge and IoT devices through standard MCP tools, bridging constrained device channels like UART, BLE, and Wi-Fi.
Connects AI assistants to physical devices via MCP, enabling LLMs to reason about sensor data, perform cross-device correlation, and interpret anomalies.