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Bacnet Mcp
What is Bacnet Mcp
bacnet-mcp is a lightweight Model Context Protocol (MCP) server designed to connect LLM agents to BACnet devices securely and in a standardized manner, facilitating the integration of AI-driven workflows with Building Automation (BAS), Building Management (BMS), and Industrial Control (ICS) systems.
Use cases
Use cases for bacnet-mcp include monitoring environmental sensors in smart buildings, automating HVAC systems, managing lighting controls, and orchestrating complex industrial processes through AI-driven agents.
How to use
To use bacnet-mcp, first install the dependency manager ‘uv’ using the provided curl command. Then clone the repository, navigate to the project directory, and run ‘uv sync’ to install dependencies. Finally, start the server with ‘uv run bacnet-mcp’ and connect to it using the MCP Inspector at ‘http://127.0.0.1:8000/mcp/’.
Key features
Key features of bacnet-mcp include secure and standardized communication with BACnet devices, real-time monitoring of sensor data, device actuation capabilities, and orchestration of complex automation tasks, all facilitated by AI-driven workflows.
Where to use
bacnet-mcp can be used in various fields including Building Automation Systems (BAS), Building Management Systems (BMS), and Industrial Control Systems (ICS), where integration of AI and automation is required.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Bacnet Mcp
bacnet-mcp is a lightweight Model Context Protocol (MCP) server designed to connect LLM agents to BACnet devices securely and in a standardized manner, facilitating the integration of AI-driven workflows with Building Automation (BAS), Building Management (BMS), and Industrial Control (ICS) systems.
Use cases
Use cases for bacnet-mcp include monitoring environmental sensors in smart buildings, automating HVAC systems, managing lighting controls, and orchestrating complex industrial processes through AI-driven agents.
How to use
To use bacnet-mcp, first install the dependency manager ‘uv’ using the provided curl command. Then clone the repository, navigate to the project directory, and run ‘uv sync’ to install dependencies. Finally, start the server with ‘uv run bacnet-mcp’ and connect to it using the MCP Inspector at ‘http://127.0.0.1:8000/mcp/’.
Key features
Key features of bacnet-mcp include secure and standardized communication with BACnet devices, real-time monitoring of sensor data, device actuation capabilities, and orchestration of complex automation tasks, all facilitated by AI-driven workflows.
Where to use
bacnet-mcp can be used in various fields including Building Automation Systems (BAS), Building Management Systems (BMS), and Industrial Control Systems (ICS), where integration of AI and automation is required.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
BACnet MCP Server
A lightweight Model Context Protocol (MCP) server that connects LLM agents to BACnet devices in a secure, standardized way, enabling seamless integration of AI-driven workflows with Building Automation (BAS), Building Management (BMS) and Industrial Control (ICS) systems, allowing agents to monitor real-time sensor data, actuate devices, and orchestrate complex automation tasks.
Getting Started
The server is built with FastMCP 2.0 and uses uv for project and dependency management. Simply run the following command to install uv or check out the installation guide for more details and alternative installation methods.
curl -LsSf https://astral.sh/uv/install.sh | sh
Clone the repository, then use uv to install project dependencies and create a virtual environment.
git clone https://github.com/ezhuk/bacnet-mcp.git
cd bacnet-mcp
uv sync
Start the BACnet MCP server by running the following command in your terminal. It defaults to using the Streamable HTTP transport on port 8000.
uv run bacnet-mcp
To confirm the server is up and running and explore available resources and tools, run the MCP Inspector and connect it to the BACnet MCP server at http://127.0.0.1:8000/mcp/. Make sure to set the transport to Streamable HTTP.
npx @modelcontextprotocol/inspector
Core Concepts
The BACnet MCP server leverages FastMCP 2.0’s core building blocks - resource templates, tools, and prompts - to streamline BACnet read and write operations with minimal boilerplate and a clean, Pythonic interface.
Read Properties
Each object on a device is mapped to a resource (and exposed as a tool) and resource templates are used to specify connection details (host, port) and read parameters (instance, property).
@mcp.resource("udp://{host}:{port}/{obj}/{instance}/{prop}")
@mcp.tool(
annotations={
"title": "Read Property",
"readOnlyHint": True,
"openWorldHint": True,
}
)
async def read_property(
host: str = settings.bacnet.host,
port: int = settings.bacnet.port,
obj: str = "analogValue",
instance: str = "1",
prop: str = "presentValue",
) -> str:
"""Reads the content of a BACnet object property on a remote unit."""
...
Write Properties
Write operations are exposed as a tool, accepting the same connection details (host, port) and allowing to set the content of an object property in a single, atomic call.
@mcp.tool(
annotations={
"title": "Write Property",
"readOnlyHint": False,
"openWorldHint": True,
}
)
async def write_property(
host: str = settings.bacnet.host,
port: int = settings.bacnet.port,
obj: str = "analogValue,1",
prop: str = "presentValue",
data: str = "1.0",
) -> str:
"""Writes a BACnet object property on a remote device."""
...
Authentication
To enable Bearer Token authentication for the Streamable HTTP transport, provide the RSA public key in PEM format in the .env file. Check out the Bearer Token Authentication section for more details.
Interactive Prompts
Structured response messages are implemented using prompts that help guide the interaction, clarify missing parameters, and handle errors gracefully.
@mcp.prompt(name="bacnet_help", tags={"bacnet", "help"})
def bacnet_help() -> list[Message]:
"""Provides examples of how to use the BACnet MCP server."""
...
Here are some example text inputs that can be used to interact with the server.
Read the presentValue property of analogInput,1 at 10.0.0.4. Fetch the units property of analogInput 2. Write the value 42 to analogValue instance 1. Set the presentValue of binaryOutput 3 to True.
Examples
The examples folder contains sample projects showing how to integrate with the BACnet MCP server using various client APIs to provide tools and context to LLMs.
- openai-agents - shows how to connect to the BACnet MCP server using the OpenAI Agents SDK.
- openai - a minimal app leveraging remote MCP server support in the OpenAI Python library.
- pydantic-ai - shows how to connect to the BACnet MCP server using the PydanticAI Agent Framework.
Docker
The BACnet MCP server can be deployed as a Docker container as follows:
docker run -d \
--name bacnet-mcp \
--restart=always \
-p 8080:8000 \
--env-file .env \
ghcr.io/ezhuk/bacnet-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.
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.










