mcp-danish-energy
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| electricity_pricesA | Get current and upcoming Danish electricity spot prices (Elspot). Returns hourly prices for today and tomorrow (when available). Prices include the raw spot price, not taxes/tariffs. |
| co2_emissionsA | Get real-time CO2 emission intensity of Danish electricity production (g CO2/kWh). Updated every 5 minutes. Useful for timing energy-intensive tasks to low-carbon periods. |
| energy_mixA | Get the real-time Danish electricity production mix: wind (offshore/onshore), solar, conventional, and cross-border exchange. Updated every 5 minutes. |
| cheapest_hoursA | Find the cheapest hours to use electricity today/tomorrow. Useful for scheduling EV charging, laundry, dishwasher, heat pumps, etc. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose: cheapest_hours focuses on cost optimization, co2_emissions on carbon intensity, electricity_prices on raw spot prices, and energy_mix on production sources. There is no overlap in functionality, making tool selection straightforward for an agent.
All tool names follow a consistent snake_case pattern with descriptive, domain-specific terms (e.g., cheapest_hours, co2_emissions). The naming is uniform and predictable, enhancing readability and coherence across the toolset.
With 4 tools, the server is well-scoped for providing Danish energy data, covering key aspects like pricing, emissions, production mix, and cost optimization. Each tool earns its place without feeling excessive or insufficient for the domain.
The toolset offers complete coverage for accessing real-time Danish energy data, including prices, emissions, production mix, and cost-saving insights. There are no obvious gaps for the server's purpose, enabling agents to handle various energy-related queries effectively.