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dasclown/strompreis-mcp

Analysis updated 2026-05-18

2PythonAudience · developerComplexity · 2/5LicenseSetup · moderate

TLDR

An MCP server that gives AI assistants real-time German electricity price forecasts from SMARD, letting agents recommend the cheapest time to run appliances or charge EVs.

Mindmap

mindmap
  root((repo))
    What it does
      Electricity price forecasts
      German SMARD data
      MCP tools for AI agents
    Tools
      price_forecast
      best_hours
      db_status
    Setup
      pip install
      cron collector
      Claude Desktop config
    Tech Stack
      Python
      SQLite
      FastAPI
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What do people build with it?

USE CASE 1

Ask Claude or another AI assistant when to run your dishwasher or charge your EV based on live German electricity prices

USE CASE 2

Add a German electricity price awareness tool to a home automation AI agent

USE CASE 3

Store a rolling history of German electricity prices locally for machine learning experiments

USE CASE 4

Build a savings calculator page that compares fixed versus dynamic electricity tariffs using live SMARD data

What is it built with?

PythonSQLiteFastAPI

How does it compare?

dasclown/strompreis-mcp0-bingwu-0/live-interpreter0xkaz/llm-governance-dashboard
Stars222
LanguagePythonPythonPython
Setup difficultymoderatemoderatehard
Complexity2/52/54/5
Audiencedevelopergeneralops devops

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Requires a cron job to refresh SMARD data every 15 minutes and a compatible MCP client like Claude Desktop.

MIT license: use, modify, and distribute freely for any purpose including commercial.

In plain English

Strompreis MCP is a Python package that lets AI agents like Claude or any MCP-compatible assistant access real-time German electricity price forecasts. Strompreis is German for electricity price. The data comes from SMARD, the official German electricity market data platform run by the federal network agency. A background collector fetches new prices every fifteen minutes and stores them in a local SQLite database. The MCP server reads from that database and exposes three tools. The first tool returns a price forecast for the next one to seventy-two hours as a JSON array with timestamps, prices in cents per kilowatt-hour, a confidence indicator, and a flag for peak hours. The second tool returns a plain-text recommendation of the cheapest hours within a window, phrased so an AI can read it directly back to a user. The third tool reports the health of the local database. Practical examples in the README show an AI agent answering questions like when to run the dishwasher, whether to charge an electric car now or wait, and what the forecast looks like for tomorrow. The agent calls the appropriate tool and returns a specific, time-stamped answer. Setup involves installing the package with pip, running a setup script to initialize the database and collect the first data, and adding the server to your Claude Desktop or Cline configuration. The collector should be scheduled with a cron job to refresh every fifteen minutes. The package also includes a small website component that calculates potential savings from switching to a dynamic electricity tariff. The project is licensed under MIT.

Copy-paste prompts

Prompt 1
I want to connect strompreis-mcp to Claude Desktop so I can ask it when electricity is cheapest today. Walk me through installation and the claude_desktop_config.json entry.
Prompt 2
How do I set up the cron job to keep the strompreis-mcp database updated with new SMARD prices every 15 minutes?
Prompt 3
I want to query the best_hours tool in strompreis-mcp programmatically from a Python script. How do I call the MCP server directly?
Prompt 4
How do I run the B2C website component of strompreis-mcp to show users a savings calculation comparing fixed and dynamic electricity tariffs?

Frequently asked questions

What is strompreis-mcp?

An MCP server that gives AI assistants real-time German electricity price forecasts from SMARD, letting agents recommend the cheapest time to run appliances or charge EVs.

What language is strompreis-mcp written in?

Mainly Python. The stack also includes Python, SQLite, FastAPI.

What license does strompreis-mcp use?

MIT license: use, modify, and distribute freely for any purpose including commercial.

How hard is strompreis-mcp to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is strompreis-mcp for?

Mainly developer.

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