tibber-mcp

# Tibber MCP Server This is a [Model Context Protocol (MCP)](https://modelcontextprotocol.io/introduction) Server for [Tibber](https://tibber.com/), a Norwegian power supplier. You can run the MCP server locally and access it via different hosts such as Claude Desktop or [Roo Code](https://marketplace.visualstudio.com/items?itemName=RooVeterinaryInc.roo-cline). For more details, check out my blog post: [Building a Tibber MCP Server: Connect Your AI Agent to Energy Consumption Data](https://feng.lu/2025/03/28/Building-a-Tibber-MCP-Server-Connect-Your-AI-Agent-to-Energy-Consumption-Data/) ## Overview The Tibber MCP server provides an AI agent with a convenient way to interact with the [Tibber API](https://developer.tibber.com/docs) and query information such as current energy prices and your energy consumption data. ## Example Queries Once connected to the MCP server, you can ask questions like: - "Analyze my power consumption data and present the usual peak hours and any other interesting patterns in an easy-to-read format." - "When did I use the most power yesterday?" - "How much power did I consume yesterday at 7 AM?" - "What is the current energy price?" - "List the 3 cheapest hours of tomorrow." - "Is the energy price higher or lower tomorrow?" ## Demo video [](https://www.youtube.com/watch?v=FiqKPa9i6V4) ## Architecture  ## Requirements - Python 3.12 - Tibber API token (You can get it from [Tibber developer portal](https://developer.tibber.com/settings/access-token)) ## Installation 1. Install `uv`: ```bash # On macOS and Linux curl -LsSf https://astral.sh/uv/install.sh | sh ``` ```powershell # On Windows powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex" ``` 2. Clone this repository: ``` git clone https://github.com/linkcd/tibber-mcp.git cd tibber-mcp ``` 3. Set up the Python virtual environment and install dependencies: ``` uv venv --python 3.12 && source .venv/bin/activate && uv pip install --requirement pyproject.toml ``` ## Host Configuration In Claude Desktop or Roo Code in VS ```json { "mcpServers":{ "tibber":{ "command":"uv", "args":[ "--directory", "[PATH-TO-ROOT-OF-THE-CLONED-TIBBER-MCP-FOLDER]", "run", "server.py" ], "env":{ "TIBBER_API_TOKEN":"[YOUR-TIBBER-TOKEN]" } } } } ``` > **IMPORTANT**: Replace `[YOUR-TIBBER-TOKEN]` with your actual token. Never commit actual credentials to version control. ### Debug and test the MCP server locally Run the server locally and run [MCP inspector](https://github.com/modelcontextprotocol/inspector) against it ```bash npx @modelcontextprotocol/inspector -e TIBBER_API_TOKEN=[YOUR-TIBBER-TOKEN] python server.py ``` ### Available Tools The server exposes the following tools that LLM can use: 1. **`get_consumption_data()`**: Get the hourly consumption data for the last 30 days, such as time period, total cost, base energy cost, and consumpted kwh 2. **`get_price_and_home_info()`**: Get price info (current, today and tomorrow) and home info (owner, address, subscription...) ## License [MIT License](LICENSE) ## Acknowledgments - This tool uses Anthropic's MCP framework - Built with [FastMCP](https://github.com/jlowin/fastmcp) for server implementation - The tibber ingeratoin is based on [pyTibber](https://github.com/Danielhiversen/pyTibber) library