# mcp2mqtt

> Use this tool when you need to integrate Large Language Models (LLMs) with IoT devices and hardware systems, allowing for natural language control of devices through configurable MQTT message topics. It solves the problem of bridging the gap between LLMs and physical devices, enabling seamless interaction and control. The tool takes natural language prompts as input and outputs corresponding MQTT commands to control devices like Raspberry Pi fans or PWM controllers.

Canonical page: https://skillsregistry.net/skills/blackhker-mcp2mqtt  
JSON: https://api.skillsregistry.net/v1/skills/blackhker-mcp2mqtt

## Description

This server bridges the Model Context Protocol (MCP) to the MQTT protocol, allowing LLMs to interact with IoT devices and hardware systems through configurable message topics. It enables users to map natural language prompts to specific MQTT commands for controlling devices like Raspberry Pi fans or PWM controllers.

## Trust

- **Trust score (0–1):** 0.77
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** iot-hardware
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/vockfnmp6m)
- **Repository:** <https://github.com/BLACKHKER/mcp2mqtt>

## 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": "blackhker-mcp2mqtt"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/blackhker-mcp2mqtt` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/blackhker-mcp2mqtt/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