# Mqtt Mcp

> A Model Context Protocol (MCP) server for MQTT.

- **Type:** MCP server
- **Install:** `agentstack add mcp-ezhuk-mqtt-mcp`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [ezhuk](https://agentstack.voostack.com/s/ezhuk)
- **Installs:** 0
- **Category:** [Integrations](https://agentstack.voostack.com/c/integrations)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [ezhuk](https://github.com/ezhuk)
- **Source:** https://github.com/ezhuk/mqtt-mcp

## Install

```sh
agentstack add mcp-ezhuk-mqtt-mcp
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

## MQTT MCP Server

A lightweight [Model Context Protocol (MCP)](https://modelcontextprotocol.io) server that connects LLM agents to [MQTT](https://en.wikipedia.org/wiki/MQTT) devices in a secure, standardized way, enabling seamless integration of AI-driven workflows with Building Automation (BAS), Industrial Control (ICS) and Smart Home systems, allowing agents to monitor real-time sensor data, actuate devices, and orchestrate complex automation tasks.

[](https://github.com/ezhuk/mqtt-mcp/actions/workflows/test.yml)
[](https://codecov.io/github/ezhuk/mqtt-mcp)
[](https://pypi.org/p/mqtt-mcp)

## Getting Started

Use [uv](https://github.com/astral-sh/uv) to add and manage the MQTT MCP server as a dependency in your project, or install it directly via `uv pip install` or `pip install`. See the [Installation](https://github.com/ezhuk/mqtt-mcp/blob/main/docs/mqtt-mcp/installation.mdx) section of the documentation for full installation instructions and more details.

```bash
uv add mqtt-mcp
```

The server can be embedded in and run directly from your application. By default, it exposes a `Streamable HTTP` endpoint at `http://127.0.0.1:8000/mcp/`.

```python
# app.py
from mqtt_mcp import MQTTMCP

mcp = MQTTMCP()

if __name__ == "__main__":
    mcp.run(transport="http")
```

It can also be launched from the command line using the provided `CLI` without modifying the source code.

```bash
mqtt-mcp
```

Or in an ephemeral, isolated environment using `uvx`. Check out the [Using tools](https://docs.astral.sh/uv/guides/tools/) guide for more details.

```bash
uvx mqtt-mcp
```

### Configuration

For the use cases where most operations target a specific MQTT broker its connection settings (`host` and `port`) can be specified at runtime using environment variables so that all prompts that omit explicit connection parameters will be routed to this broker.

```bash
export MQTT_MCP_MQTT__HOST=10.0.0.1
export MQTT_MCP_MQTT__PORT=1883
```

These settings can also be specified in a `.env` file in the working directory.

```text
# .env
mqtt_mcp_mqtt__host=10.0.0.1
mqtt_mcp_mqtt__port=1883
```

### MCP Inspector

To confirm the server is up and running and explore available resources and tools, run the [MCP Inspector](https://modelcontextprotocol.io/docs/tools/inspector) and connect it to the MQTT MCP server at `http://127.0.0.1:8000/mcp/`. Make sure to set the transport to `Streamable HTTP`.

```bash
npx @modelcontextprotocol/inspector
```

## Core Concepts

The MQTT MCP server leverages FastMCP 2.0's core building blocks - resource templates, tools, and prompts - to streamline MQTT receive and publish operations with minimal boilerplate and a clean, Pythonic interface.

### Receive Message

Each topic on a device is mapped to a resource (and exposed as a tool) and [resource templates](https://gofastmcp.com/servers/resources#resource-templates) are used to specify connection details (host, port) and receive parameters (topic, timeout).

```python
@mcp.resource("mqtt://{host}:{port}/{topic*}")
@mcp.tool(
    annotations={
        "title": "Receive Message",
        "readOnlyHint": True,
        "openWorldHint": True,
    }
)
async def receive_message(
    topic: str,
    host: str = settings.mqtt.host,
    port: int = settings.mqtt.port,
    timeout: int = 60,
) -> str:
    """Receives a message published to the specified topic, if any."""
    ...
```

### Publish Message

Publish operations are exposed as a [tool](https://gofastmcp.com/servers/tools), accepting the same connection details (host, port) and allowing to publish a message to a specific topic in a single, atomic call.

```python
@mcp.tool(
    annotations={
        "title": "Publish Message",
        "readOnlyHint": False,
        "openWorldHint": True,
    }
)
async def publish_message(
    topic: str,
    message: str,
    host: str = settings.mqtt.host,
    port: int = settings.mqtt.port,
) -> str:
    """Publishes a message to the specified topic."""
    ...
```

### Authentication

To enable authentication using the built-in [AuthKit](https://www.authkit.com) provider for the `Streamable HTTP` transport, provide the AuthKit domain and redirect URL in the `.env` file. Check out the [AuthKit Provider](https://gofastmcp.com/servers/auth/remote-oauth#example%3A-workos-authkit-provider) section for more details.

### Interactive Prompts

Structured response messages are implemented using [prompts](https://gofastmcp.com/servers/prompts) that help guide the interaction, clarify missing parameters, and handle errors gracefully.

```python
@mcp.prompt(name="mqtt_help", tags={"mqtt", "help"})
def mqtt_help() -> list[Message]:
    """Provides examples of how to use the MQTT MCP server."""
    ...
```

Here are some example text inputs that can be used to interact with the server.

```text
Publish {"foo":"bar"} to topic "devices/foo" on 127.0.0.1:1883.
Receive a message from topic "devices/bar", waiting up to 30 seconds.
```

## Examples

The `examples` folder contains sample projects showing how to integrate with the MQTT MCP server using various client APIs to provide tools and context to LLMs.

- [openai-agents](https://github.com/ezhuk/mqtt-mcp/tree/main/examples/openai-agents) - shows how to connect to the MQTT MCP server using the [OpenAI Agents SDK](https://openai.github.io/openai-agents-python/mcp/).
- [openai](https://github.com/ezhuk/mqtt-mcp/tree/main/examples/openai) - a minimal app leveraging remote MCP server support in the [OpenAI Python library](https://platform.openai.com/docs/guides/tools-remote-mcp).
- [pydantic-ai](https://github.com/ezhuk/mqtt-mcp/tree/main/examples/pydantic-ai) - shows how to connect to the MQTT MCP server using the [PydanticAI Agent Framework](https://ai.pydantic.dev).

## Docker

The MQTT MCP server can be deployed as a Docker container as follows:

```bash
docker run -dit \
  --name mqtt-mcp \
  --restart=always \
  -p 8080:8000 \
  --env-file .env \
  ghcr.io/ezhuk/mqtt-mcp:latest
```

This maps port `8080` on the host to the MCP server's port `8000` inside the container and loads settings from the `.env` file, if present.

## License

The server is licensed under the [MIT License](https://github.com/ezhuk/mqtt-mcp?tab=MIT-1-ov-file).

## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [ezhuk](https://github.com/ezhuk)
- **Source:** [ezhuk/mqtt-mcp](https://github.com/ezhuk/mqtt-mcp)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** yes
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/mcp-ezhuk-mqtt-mcp
- Seller: https://agentstack.voostack.com/s/ezhuk
- Browse the marketplace: https://agentstack.voostack.com/browse

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