# MQTT Bridge

> Use this tool when you need to integrate AI agents with IoT devices, enabling real-time monitoring and control through the MQTT messaging protocol. It solves problems of device management, sensor data retrieval, and command execution for physical equipment in smart homes and industrial settings. The MQTT Bridge takes in device data and AI commands as inputs and outputs real-time sensor readings and execution results through SSE or stdio transports.

Canonical page: https://skillsregistry.net/skills/baiyanlong-mqtt  
JSON: https://api.skillsregistry.net/v1/skills/baiyanlong-mqtt

## Description

MQTT Bridge enables AI agents to control and monitor IoT devices through the MQTT messaging protocol. It supports device discovery, real-time sensor data retrieval, and command execution for physical equipment. The lightweight Rust binary runs on edge devices like Raspberry Pi and communicates using SSE or stdio transports, bridging cloud AI with factory floor equipment and smart home devices.

## Trust

- **Trust score (0–1):** 0.36
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** iot-hardware
- **Updated:** 2026-09-01

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/baiyanlong-mqtt)
- **Repository:** <https://github.com/baiyanlong/mqtt-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "baiyanlong-mqtt"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/baiyanlong-mqtt` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/baiyanlong-mqtt/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt