An AI agent system that monitors manufacturing equipment health using the Model Context Protocol (MCP). Enables answering natural language questions about equipment status, maintenance, and anomalies through MCP tools.
Enables AI-assisted chiller troubleshooting by exposing MCP tools to retrieve operational data, alarms, telemetry, and service history from MongoDB Atlas, plus vector and hybrid search over knowledge bases.
Exposes live industrial IoT telemetry to any MCP client, streaming simulated sensor data from a fleet of machines and detecting anomalies, with the ability to inject faults on demand.
Connect your AI workflows to the ThingsBoard IoT Platform through this MCP server.
Enables LLMs to query device telemetry, manage IoT entities (devices, assets, customers), and analyze sensor data - all through natural language.
Perfect for building AI-powered IoT monitoring, predictive maintenance,
MCP server for PTC ThingWorx, the IIoT platform, providing 8 tools for AI agents to read live state and trigger actions across the industrial asset graph with env-gated safety for writes and invocations.
